Bioinformatics () is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.

Computational, statistical, and computer programming techniques have been used  for computer simulation analyses of biological queries. They include reused specific analysis "pipelines", particularly in the field of genomics, such as by the identification of genes and single nucleotide polymorphisms (SNPs). These pipelines are used to better understand the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. Bioinformatics also includes proteomics, which tries to understand the organizational principles within nucleic acid and protein sequences.

Image and signal processing allow extraction of useful results from large amounts of raw data. In the field of genetics, it aids in sequencing and annotating genomes and their observed mutations. Bioinformatics includes text mining of biological literature and the development of biological and gene ontologies to organize and query biological data. It also plays a role in the analysis of gene and protein expression and regulation. Bioinformatics tools aid in comparing, analyzing and interpreting genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology. At a more integrative level, it helps analyze and catalogue the biological pathways and networks that are an important part of systems biology. In structural biology, it aids in the simulation and modeling of DNA, RNA, proteins as well as biomolecular interactions.

History
The first definition of the term bioinformatics was coined by Paulien Hogeweg and Ben Hesper in 1970, to refer to the study of information processes in biotic systems. This definition placed bioinformatics as a field parallel to biochemistry (the study of chemical processes in biological systems).

Bioinformatics and computational biology involved the analysis of biological data, particularly DNA, RNA, and protein sequences. The field of bioinformatics experienced explosive growth starting in the mid-1990s, driven largely by the Human Genome Project and by rapid advances in DNA sequencing technology.

Analyzing biological data to produce meaningful information involves writing and running software programs that use algorithms from graph theory, artificial intelligence, soft computing, data mining, image processing, and computer simulation. The algorithms in turn depend on theoretical foundations such as discrete mathematics, control theory, system theory, information theory, and statistics.

Sequences

There has been a tremendous advance in speed and cost reduction since the completion of the Human Genome Project, with some labs able to sequence over 100,000 billion bases each year, and a full genome can be sequenced for $1,000 or less.

Computers became essential in molecular biology when protein sequences became available after Frederick Sanger determined the sequence of insulin in the early 1950s. Comparing multiple sequences manually turned out to be impractical. Margaret Oakley Dayhoff, a pioneer in the field, compiled one of the first protein sequence databases, initially published as books as well as methods of sequence alignment and molecular evolution. Another early contributor to bioinformatics was Elvin A. Kabat, who pioneered biological sequence analysis in 1970 with his comprehensive volumes of antibody sequences released online with Tai Te Wu between 1980 and 1991.

In the 1970s, new techniques for sequencing DNA were applied to bacteriophage MS2 and øX174, and the extended nucleotide sequences were then parsed with informational and statistical algorithms. These studies illustrated that well known features, such as the coding segments and the triplet code, are revealed in straightforward statistical analyses and were the proof of the concept that bioinformatics would be insightful.

Goals
In order to study how normal cellular activities are altered in different disease states, raw biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data. This also includes nucleotide and amino acid sequences, protein domains, and protein structures.

Important sub-disciplines within bioinformatics and computational biology include:

 Development and implementation of computer programs to efficiently access, manage, and use various types of information.
 Development of new mathematical algorithms and statistical measures to assess relationships among members of large data sets. For example, there are methods to locate a gene within a sequence, to predict protein structure and/or function, and to cluster protein sequences into families of related sequences.

The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches is its focus on developing and applying computationally intensive techniques to achieve this goal. Examples include: pattern recognition, data mining, machine learning algorithms, and visualization. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein–protein interactions, genome-wide association studies, the modeling of evolution and cell division/mitosis.

Bioinformatics entails the creation and advancement of databases, algorithms, computational and statistical techniques, and theory to solve formal and practical problems arising from the management and analysis of biological data.

Over the past few decades, rapid developments in genomic and other molecular research technologies and developments in information technologies have combined to produce a tremendous amount of information related to molecular biology. Bioinformatics is the name given to these mathematical and computing approaches used to glean understanding of biological processes.

Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures.

Sequence analysis

Since the bacteriophage Phage Φ-X174 was sequenced in 1977, the DNA sequences of thousands of organisms have been decoded and stored in databases. This sequence information is analyzed to determine genes that encode proteins, RNA genes, regulatory sequences, structural motifs, and repetitive sequences. A comparison of genes within a species or between different species can show similarities between protein functions, or relations between species (the use of molecular systematics to construct phylogenetic trees). With the growing amount of data, it long ago became impractical to analyze DNA sequences manually. Computer programs such as BLAST are used routinely to search sequences—as of 2008, from more than 260,000 organisms, containing over 190 billion nucleotides.

DNA sequencing

Before sequences can be analyzed, they are obtained from a data storage bank, such as GenBank. DNA sequencing is still a non-trivial problem as the raw data may be noisy or affected by weak signals. Algorithms have been developed for base calling for the various experimental approaches to DNA sequencing.

Sequence assembly

Most DNA sequencing techniques produce short fragments of sequence that need to be assembled to obtain complete gene or genome sequences. The shotgun sequencing technique (used by The Institute for Genomic Research (TIGR) to sequence the first bacterial genome, Haemophilus influenzae) generates the sequences of many thousands of small DNA fragments (ranging from 35 to 900 nucleotides long, depending on the sequencing technology). The ends of these fragments overlap and, when aligned properly by a genome assembly program, can be used to reconstruct the complete genome. Shotgun sequencing yields sequence data quickly, but the task of assembling the fragments can be quite complicated for larger genomes. For a genome as large as the human genome, it may take many days of CPU time on large-memory, multiprocessor computers to assemble the fragments, and the resulting assembly usually contains numerous gaps that must be filled in later. Shotgun sequencing is the method of choice for virtually all genomes sequenced (rather than chain-termination or chemical degradation methods), and genome assembly algorithms are a critical area of bioinformatics research.

Genome annotation

In genomics, annotation refers to the process of marking the stop and start regions of genes and other biological features in a sequenced DNA sequence. Many genomes are too large to be annotated by hand. As the rate of sequencing exceeds the rate of genome annotation, genome annotation has become the new bottleneck in bioinformatics.

Genome annotation can be classified into three levels: the nucleotide, protein, and process levels.

Gene finding is a chief aspect of nucleotide-level annotation. For complex genomes, a combination of ab initio gene prediction and sequence comparison with expressed sequence databases and other organisms can be successful. Nucleotide-level annotation also allows the integration of genome sequence with other genetic and physical maps of the genome.

The principal aim of protein-level annotation is to assign function to the protein products of the genome. Databases of protein sequences and functional domains and motifs are used for this type of annotation. About half of the predicted proteins in a new genome sequence tend to have no obvious function.

Understanding the function of genes and their products in the context of cellular and organismal physiology is the goal of process-level annotation. An obstacle of process-level annotation has been the inconsistency of terms used by different model systems. The Gene Ontology Consortium is helping to solve this problem.

The first description of a comprehensive annotation system was published in 1995 by The Institute for Genomic Research, which performed the first complete sequencing and analysis of the genome of a free-living (non-symbiotic) organism, the bacterium Haemophilus influenzae. The system identifies the genes encoding all proteins, transfer RNAs, ribosomal RNAs, in order to make initial functional assignments. The GeneMark program trained to find protein-coding genes in Haemophilus influenzae is constantly changing and improving.

Following the goals that the Human Genome Project left to achieve after its closure in 2003, the ENCODE project was developed by the National Human Genome Research Institute. This project is a collaborative data collection of the functional elements of the human genome that uses next-generation DNA-sequencing technologies and genomic tiling arrays, technologies able to automatically generate large amounts of data at a dramatically reduced per-base cost but with the same accuracy (base call error) and fidelity (assembly error).

Gene function prediction
While genome annotation is primarily based on sequence similarity (and thus homology), other properties of sequences can be used to predict the function of genes. In fact, most gene function prediction methods focus on protein sequences as they are more informative and more feature-rich. For instance, the distribution of hydrophobic amino acids predicts transmembrane segments in proteins. However, protein function prediction can also use external information such as gene (or protein) expression data, protein structure, or protein-protein interactions.

Computational evolutionary biology

Evolutionary biology is the study of the origin and descent of species, as well as their change over time. Informatics has assisted evolutionary biologists by enabling researchers to:
 trace the evolution of a large number of organisms by measuring changes in their DNA, rather than through physical taxonomy or physiological observations alone,
 compare entire genomes, which permits the study of more complex evolutionary events, such as gene duplication, horizontal gene transfer, and the prediction of factors important in bacterial speciation,
 build complex computational population genetics models to predict the outcome of the system over time
 track and share information on an increasingly large number of species and organisms
Future work endeavours to reconstruct the now more complex tree of life.

Comparative genomics

The core of comparative genome analysis is the establishment of the correspondence between genes (orthology analysis) or other genomic features in different organisms. Intergenomic maps are made to trace the evolutionary processes responsible for the divergence of two genomes. A multitude of evolutionary events acting at various organizational levels shape genome evolution. At the lowest level, point mutations affect individual nucleotides. At a higher level, large chromosomal segments undergo duplication, lateral transfer, inversion, transposition, deletion and insertion. Entire genomes are involved in processes of hybridization, polyploidization and endosymbiosis that lead to rapid speciation. The complexity of genome evolution poses many exciting challenges to developers of mathematical models and algorithms, who have recourse to a spectrum of algorithmic, statistical and mathematical techniques, ranging from exact, heuristics, fixed parameter and approximation algorithms for problems based on parsimony models to Markov chain Monte Carlo algorithms for Bayesian analysis of problems based on probabilistic models.

Many of these studies are based on the detection of sequence homology to assign sequences to protein families.

Pan genomics

Pan genomics is a concept introduced in 2005 by Tettelin and Medini. Pan genome is the complete gene repertoire of a particular monophyletic taxonomic group. Although initially applied to closely related strains of a species, it can be applied to a larger context like genus, phylum, etc. It is divided in two parts: the Core genome, a set of genes common to all the genomes under study (often housekeeping genes vital for survival), and the Dispensable/Flexible genome: a set of genes not present in all but one or some genomes under study. A bioinformatics tool BPGA can be used to characterize the Pan Genome of bacterial species.

Genetics of disease

As of 2013, the existence of efficient high-throughput next-generation sequencing technology allows for the identification of cause many different human disorders. Simple Mendelian inheritance has been observed for over 3,000 disorders that have been identified at the Online Mendelian Inheritance in Man database, but complex diseases are more difficult. Association studies have found many individual genetic regions that individually are weakly associated with complex diseases (such as infertility, breast cancer and Alzheimer's disease), rather than a single cause. There are currently many challenges to using genes for diagnosis and treatment, such as how we don't know which genes are important, or how stable the choices an algorithm provides.

Genome-wide association studies have successfully identified thousands of common genetic variants for complex diseases and traits; however, these common variants only explain a small fraction of heritability. Rare variants may account for some of the missing heritability. Large-scale whole genome sequencing studies have rapidly sequenced millions of whole genomes, and such studies have identified hundreds of millions of rare variants. Functional annotations predict the effect or function of a genetic variant and help to prioritize rare functional variants, and incorporating these annotations can effectively boost the power of genetic association of rare variants analysis of whole genome sequencing studies. Some tools have been developed to provide all-in-one rare variant association analysis for whole-genome sequencing data, including integration of genotype data and their functional annotations, association analysis, result summary and visualization. Meta-analysis of whole genome sequencing studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes.

Analysis of mutations in cancer

In cancer, the genomes of affected cells are rearranged in complex or unpredictable ways. In addition to single-nucleotide polymorphism arrays identifying point mutations that cause cancer, oligonucleotide microarrays can be used to identify chromosomal gains and losses (called comparative genomic hybridization). These detection methods generate terabytes of data per experiment. The data is often found to contain considerable variability, or noise, and thus Hidden Markov model and change-point analysis methods are being developed to infer real copy number changes.

Two important principles can be used to identify cancer by mutations in the exome. First, cancer is a disease of accumulated somatic mutations in genes. Second, cancer contains driver mutations which need to be distinguished from passengers.

Further improvements in bioinformatics could allow for classifying types of cancer by analysis of cancer driven mutations in the genome. Furthermore, tracking of patients while the disease progresses may be possible in the future with the sequence of cancer samples. Another type of data that requires novel informatics development is the analysis of lesions found to be recurrent among many tumors.

Gene and protein expression

Analysis of gene expression
The expression of many genes can be determined by measuring mRNA levels with multiple techniques including microarrays, expressed cDNA sequence tag (EST) sequencing, serial analysis of gene expression (SAGE) tag sequencing, massively parallel signature sequencing (MPSS), RNA-Seq, also known as "Whole Transcriptome Shotgun Sequencing" (WTSS), or various applications of multiplexed in-situ hybridization. All of these techniques are extremely noise-prone and/or subject to bias in the biological measurement, and a major research area in computational biology involves developing statistical tools to separate signal from noise in high-throughput gene expression studies. Such studies are often used to determine the genes implicated in a disorder: one might compare microarray data from cancerous epithelial cells to data from non-cancerous cells to determine the transcripts that are up-regulated and down-regulated in a particular population of cancer cells.

Analysis of protein expression
Protein microarrays and high throughput (HT) mass spectrometry (MS) can provide a snapshot of the proteins present in a biological sample. The former approach faces similar problems as with microarrays targeted at mRNA, the latter involves the problem of matching large amounts of mass data against predicted masses from protein sequence databases, and the complicated statistical analysis of samples when multiple incomplete peptides from each protein are detected. Cellular protein localization in a tissue context can be achieved through affinity proteomics displayed as spatial data based on immunohistochemistry and tissue microarrays.

Analysis of regulation
Gene regulation is a complex process where a signal, such as an extracellular signal such as a hormone, eventually leads to an increase or decrease in the activity of one or more proteins. Bioinformatics techniques have been applied to explore various steps in this process.

For example, gene expression can be regulated by nearby elements in the genome. Promoter analysis involves the identification and study of sequence motifs in the DNA surrounding the protein-coding region of a gene. These motifs influence the extent to which that region is transcribed into mRNA. Enhancer elements far away from the promoter can also regulate gene expression, through three-dimensional looping interactions. These interactions can be determined by bioinformatic analysis of chromosome conformation capture experiments.

Expression data can be used to infer gene regulation: one might compare microarray data from a wide variety of states of an organism to form hypotheses about the genes involved in each state. In a single-cell organism, one might compare stages of the cell cycle, along with various stress conditions (heat shock, starvation, etc.). Clustering algorithms can be then applied to expression data to determine which genes are co-expressed. For example, the upstream regions (promoters) of co-expressed genes can be searched for over-represented regulatory elements. Examples of clustering algorithms applied in gene clustering are k-means clustering, self-organizing maps (SOMs), hierarchical clustering, and consensus clustering methods.

Analysis of cellular organization
Several approaches have been developed to analyze the location of organelles, genes, proteins, and other components within cells. A gene ontology category, cellular component, has been devised to capture subcellular localization in many biological databases.

Microscopy and image analysis
Microscopic pictures allow for the location of organelles as well as molecules, which may be the source of abnormalities in diseases.

Protein localization
Finding the location of proteins allows us to predict what they do. This is called protein function prediction. For instance, if a protein is found in the nucleus it may be involved in gene regulation or splicing. By contrast, if a protein is found in mitochondria, it may be involved in respiration or other metabolic processes. There are well developed protein subcellular localization prediction resources available, including protein subcellular location databases, and prediction tools.

Nuclear organization of chromatin

Data from high-throughput chromosome conformation capture experiments, such as Hi-C (experiment) and ChIA-PET, can provide information on the three-dimensional structure and nuclear organization of chromatin. Bioinformatic challenges in this field include partitioning the genome into domains, such as Topologically Associating Domains (TADs), that are organised together in three-dimensional space.

Structural bioinformatics

Finding the structure of proteins is an important application of bioinformatics. The Critical Assessment of Protein Structure Prediction (CASP) is an open competition where worldwide research groups submit protein models for evaluating unknown protein models.

Amino acid sequence
The linear amino acid sequence of a protein is called the primary structure. The primary structure can be easily determined from the sequence of codons on the DNA gene that codes for it. In most proteins, the primary structure uniquely determines the 3-dimensional structure of a protein in its native environment. An exception is the misfolded protein involved in bovine spongiform encephalopathy. This structure is linked to the function of the protein. Additional structural information includes the secondary, tertiary and quaternary structure. A viable general solution to the prediction of the function of a protein remains an open problem. Most efforts have so far been directed towards heuristics that work most of the time.

Homology
In the genomic branch of bioinformatics, homology is used to predict the function of a gene: if the sequence of gene A, whose function is known, is homologous to the sequence of gene B, whose function is unknown, one could infer that B may share A's function. In structural bioinformatics, homology is used to determine which parts of a protein are important in structure formation and interaction with other proteins. Homology modeling is used to predict the structure of an unknown protein from existing homologous proteins.

One example of this is hemoglobin in humans and the hemoglobin in legumes (leghemoglobin), which are distant relatives from the same protein superfamily. Both serve the same purpose of transporting oxygen in the organism. Although both of these proteins have completely different amino acid sequences, their protein structures are virtually identical, which reflects their near identical purposes and shared ancestor.

Other techniques for predicting protein structure include protein threading and de novo (from scratch) physics-based modeling.

Another aspect of structural bioinformatics include the use of protein structures for Virtual Screening models such as Quantitative Structure-Activity Relationship models and proteochemometric models (PCM). Furthermore, a protein's crystal structure can be used in simulation of for example ligand-binding studies and in silico mutagenesis studies.

A 2021 deep-learning algorithms-based software called AlphaFold, developed by Google's DeepMind, greatly outperforms all other prediction software methods, and has released predicted structures for hundreds of millions of proteins in the AlphaFold protein structure database.

Network and systems biology

Network analysis seeks to understand the relationships within biological networks such as metabolic or protein–protein interaction networks. Although biological networks can be constructed from a single type of molecule or entity (such as genes), network biology often attempts to integrate many different data types, such as proteins, small molecules, gene expression data, and others, which are all connected physically, functionally, or both.

Systems biology involves the use of computer simulations of cellular subsystems (such as the networks of metabolites and enzymes that comprise metabolism, signal transduction pathways and gene regulatory networks) to both analyze and visualize the complex connections of these cellular processes. Artificial life or virtual evolution attempts to understand evolutionary processes via the computer simulation of simple (artificial) life forms.

Molecular interaction networks

Tens of thousands of three-dimensional protein structures have been determined by X-ray crystallography and protein nuclear magnetic resonance spectroscopy (protein NMR) and a central question in structural bioinformatics is whether it is practical to predict possible protein–protein interactions only based on these 3D shapes, without performing protein–protein interaction experiments. A variety of methods have been developed to tackle the protein–protein docking problem, though it seems that there is still much work to be done in this field.

Other interactions encountered in the field include Protein–ligand (including drug) and protein–peptide. Molecular dynamic simulation of movement of atoms about rotatable bonds is the fundamental principle behind computational algorithms, termed docking algorithms, for studying molecular interactions.

Biodiversity informatics

Biodiversity informatics deals with the collection and analysis of biodiversity data, such as taxonomic databases, or microbiome data. Examples of such analyses include phylogenetics, niche modelling, species richness mapping, DNA barcoding, or species identification tools. A growing area is also macro-ecology, i.e. the study of how biodiversity is connected to ecology and human impact, such as climate change.

Others

Literature analysis

The enormous number of published literature makes it virtually impossible for individuals to read every paper, resulting in disjointed sub-fields of research. Literature analysis aims to employ computational and statistical linguistics to mine this growing library of text resources. For example:
 Abbreviation recognition – identify the long-form and abbreviation of biological terms
 Named-entity recognition – recognizing biological terms such as gene names
 Protein–protein interaction – identify which proteins interact with which proteins from text

The area of research draws from statistics and computational linguistics.

High-throughput image analysis
Computational technologies are used to automate the processing, quantification and analysis of large amounts of high-information-content biomedical imagery. Modern image analysis systems can improve an observer's accuracy, objectivity, or speed. Image analysis is important for both diagnostics and research. Some examples are:
 high-throughput and high-fidelity quantification and sub-cellular localization (high-content screening, cytohistopathology, Bioimage informatics)
 morphometrics
 clinical image analysis and visualization
 determining the real-time air-flow patterns in breathing lungs of living animals
 quantifying occlusion size in real-time imagery from the development of and recovery during arterial injury
 making behavioral observations from extended video recordings of laboratory animals
 infrared measurements for metabolic activity determination
 inferring clone overlaps in DNA mapping, e.g. the Sulston score

High-throughput single cell data analysis

Computational techniques are used to analyse high-throughput, low-measurement single cell data, such as that obtained from flow cytometry. These methods typically involve finding populations of cells that are relevant to a particular disease state or experimental condition.

Ontologies and data integration
Biological ontologies are directed acyclic graphs of controlled vocabularies. They create categories for biological concepts and descriptions so they can be easily analyzed with computers. When categorised in this way, it is possible to gain added value from holistic and integrated analysis.

The OBO Foundry was an effort to standardise certain ontologies. One of the most widespread is the Gene ontology which describes gene function. There are also ontologies which describe phenotypes.

Databases

Databases are essential for bioinformatics research and applications. Databases exist for many different information types, including DNA and protein sequences, molecular structures, phenotypes and biodiversity. Databases can contain both empirical data (obtained directly from experiments) and predicted data (obtained from analysis of existing data). They may be specific to a particular organism, pathway or molecule of interest. Alternatively, they can incorporate data compiled from multiple other databases. Databases can have different formats, access mechanisms, and be public or private.

Some of the most commonly used databases are listed below:

 Used in biological sequence analysis: Genbank, UniProt
 Used in structure analysis: Protein Data Bank (PDB)
 Used in finding Protein Families and Motif Finding: InterPro, Pfam
 Used for Next Generation Sequencing: Sequence Read Archive
 Used in Network Analysis: Metabolic Pathway Databases (KEGG, BioCyc), Interaction Analysis Databases, Functional Networks
 Used in design of synthetic genetic circuits: GenoCAD

Software and tools
Software tools for bioinformatics include simple command-line tools, more complex graphical programs, and standalone web-services. They are made by bioinformatics companies or by public institutions.

Open-source bioinformatics software

Many free and open-source software tools have existed and continued to grow since the 1980s. The combination of a continued need for new algorithms for the analysis of emerging types of biological readouts, the potential for innovative in silico experiments, and freely available open code bases have created opportunities for research groups to contribute to both bioinformatics regardless of funding. The open source tools often act as incubators of ideas, or community-supported plug-ins in commercial applications. They may also provide de facto standards and shared object models for assisting with the challenge of bioinformation integration.

Open-source bioinformatics software includes Bioconductor, BioPerl, Biopython, BioJava, BioJS, BioRuby, Bioclipse, EMBOSS, .NET Bio, Orange with its bioinformatics add-on, Apache Taverna, UGENE and GenoCAD.

The non-profit Open Bioinformatics Foundation and the annual Bioinformatics Open Source Conference promote open-source bioinformatics software.

Web services in bioinformatics
SOAP- and REST-based interfaces have been developed to allow client computers to use algorithms, data and computing resources from servers in other parts of the world. The main advantage are that end users do not have to deal with software and database maintenance overheads.

Basic bioinformatics services are classified by the EBI into three categories: SSS (Sequence Search Services), MSA (Multiple Sequence Alignment), and BSA (Biological Sequence Analysis). The availability of these service-oriented bioinformatics resources demonstrate the applicability of web-based bioinformatics solutions, and range from a collection of standalone tools with a common data format under a single web-based interface, to integrative, distributed and extensible bioinformatics workflow management systems.

Bioinformatics workflow management systems

A bioinformatics workflow management system is a specialized form of a workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or a workflow, in a Bioinformatics application. Such systems are designed to
 provide an easy-to-use environment for individual application scientists themselves to create their own workflows,
 provide interactive tools for the scientists enabling them to execute their workflows and view their results in real-time,
 simplify the process of sharing and reusing workflows between the scientists, and
 enable scientists to track the provenance of the workflow execution results and the workflow creation steps.

Some of the platforms giving this service: Galaxy, Kepler, Taverna, UGENE, Anduril, HIVE.

BioCompute and BioCompute Objects
In 2014, the US Food and Drug Administration sponsored a conference held at the National Institutes of Health Bethesda Campus to discuss reproducibility in bioinformatics. Over the next three years, a consortium of stakeholders met regularly to discuss what would become BioCompute paradigm. These stakeholders included representatives from government, industry, and academic entities. Session leaders represented numerous branches of the FDA and NIH Institutes and Centers, non-profit entities including the Human Variome Project and the European Federation for Medical Informatics, and research institutions including Stanford, the New York Genome Center, and the George Washington University.

It was decided that the BioCompute paradigm would be in the form of digital 'lab notebooks' which allow for the reproducibility, replication, review, and reuse, of bioinformatics protocols. This was proposed to enable greater continuity within a research group over the course of normal personnel flux while furthering the exchange of ideas between groups. The US FDA funded this work so that information on pipelines would be more transparent and accessible to their regulatory staff.

In 2016, the group reconvened at the NIH in Bethesda and discussed the potential for a BioCompute Object, an instance of the BioCompute paradigm. This work was copied as both a "standard trial use" document and a preprint paper uploaded to bioRxiv. The BioCompute object allows for the JSON-ized record to be shared among employees, collaborators, and regulators.

Education platforms
Bioinformatics is not only taught as in-person masters degree at many universities. The computational nature of bioinformatics lends it to computer-aided and online learning. Software platforms designed to teach bioinformatics concepts and methods include Rosalind and online courses offered through the Swiss Institute of Bioinformatics Training Portal. The Canadian Bioinformatics Workshops provides videos and slides from training workshops on their website under a Creative Commons license. The 4273π project or 4273pi project also offers open source educational materials for free. The course runs on low cost Raspberry Pi computers and has been used to teach adults and school pupils. 4283 is actively developed by a consortium of academics and research staff who have run research level bioinformatics using Raspberry Pi computers and the 4283π operating system.

MOOC platforms also provide online certifications in bioinformatics and related disciplines, including Coursera's Bioinformatics Specialization (UC San Diego) and Genomic Data Science Specialization (Johns Hopkins) as well as EdX's Data Analysis for Life Sciences XSeries (Harvard).

Conferences
There are several large conferences that are concerned with bioinformatics. Some of the most notable examples are Intelligent Systems for Molecular Biology (ISMB), European Conference on Computational Biology (ECCB), and Research in Computational Molecular Biology (RECOMB).

See also

References

Further reading

 Sehgal et al. : Structural, phylogenetic and docking studies of D-amino acid oxidase activator(DAOA ), a candidate schizophrenia gene. Theoretical Biology and Medical Modelling 2013 10 :3.
 Achuthsankar S Nair Computational Biology & Bioinformatics – A gentle Overview , Communications of Computer Society of India, January 2007
 Aluru, Srinivas, ed. Handbook of Computational Molecular Biology. Chapman & Hall/Crc, 2006.  (Chapman & Hall/Crc Computer and Information Science Series)
 Baldi, P and Brunak, S, Bioinformatics: The Machine Learning Approach, 2nd edition. MIT Press, 2001.
 Barnes, M.R. and Gray, I.C., eds., Bioinformatics for Geneticists, first edition. Wiley, 2003.
 Baxevanis, A.D. and Ouellette, B.F.F., eds., Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, third edition. Wiley, 2005.
 Baxevanis, A.D., Petsko, G.A., Stein, L.D., and Stormo, G.D., eds., Current Protocols in Bioinformatics. Wiley, 2007.
 Cristianini, N. and Hahn, M. Introduction to Computational Genomics , Cambridge University Press, 2006. ( |)
 Durbin, R., S. Eddy, A. Krogh and G. Mitchison, Biological sequence analysis. Cambridge University Press, 1998.

 Keedwell, E., Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems. Wiley, 2005.
 Kohane, et al. Microarrays for an Integrative Genomics. The MIT Press, 2002.
 Lund, O. et al. Immunological Bioinformatics. The MIT Press, 2005.
 Pachter, Lior and Sturmfels, Bernd. "Algebraic Statistics for Computational Biology" Cambridge University Press, 2005.
 Pevzner, Pavel A. Computational Molecular Biology: An Algorithmic Approach The MIT Press, 2000.
 Soinov, L. Bioinformatics and Pattern Recognition Come Together  Journal of Pattern Recognition Research (JPRR ), Vol 1 (1) 2006 p. 37–41
 Stevens, Hallam, Life Out of Sequence: A Data-Driven History of Bioinformatics, Chicago: The University of Chicago Press, 2013,
 Tisdall, James. "Beginning Perl for Bioinformatics" O'Reilly, 2001.
 Catalyzing Inquiry at the Interface of Computing and Biology (2005) CSTB report
 Calculating the Secrets of Life: Contributions of the Mathematical Sciences and computing to Molecular Biology (1995)
 Foundations of Computational and Systems Biology MIT Course
 Computational Biology: Genomes, Networks, Evolution Free MIT Course

External links

Bioinformatics Resource Portal (SIB)

Bioinformatics


In linguistics, noun phrases have grammatical number. Singular is one kind of grammatical number. A singular noun phrase usually refers to something that you would count as one only (e.g., one time, a glass, the sun, my mother, Jennifer). Noun phrases that cannot be counted are also singular in English (e.g., water, the meat, some space, etc.). In contrast, plural noun phrases are counted as more or less than one (e.g., no bananas, 0.5 liters, 1.2 grams, two times, three fish, 20 mothers).

Grammar

Singular


Craig Ward Anton (born August 28, 1962 in Omaha, Nebraska) is an American actor and comedian. Anton is most notable for being the cast of comedians on the show MADtv and for his role as Lloyd Diffy in the Disney Channel Original Series Phil of the Future.

Biography
Craig was born and raised in Omaha, Nebraska. He is the oldest son of Arthur and Antoinette Anton and of four children. Craig has two younger sisters, Toni (born 1964) and Megan (born 1977), and one younger brother, Brian (1970). Craig's parents are divorced and his father remarried. He is now married to Eileen McBay and they now live in Houston, Texas, while his mother lives in Las Vegas, Nevada.

Early life and career
Craig attended R.M. Marrs junior high school. He graduated from Burke High School in 1980 and attended University of Nebraska at Kearney. Craig begin his career as a college circuit comedian in the 1980s. In 1984, he traveled the Mediterranean and Middle East as part of the USO comedy tour, where he spent two months in Turkey, Greece, Italy, Israel, Bahrain, and Spain entertaining our troops and in 1985, he was named Showtime's Funniest Person in Nebraska. Craig was nominated from the NACA Campus Entertainer of the Year award three times.

MADtv
During his three-year tenure, Anton received limited screentime on the show. He primarily did a stand-up segment during some episodes. Aside from his stand-up routine, Anton was often cast as an extra or supporting character. Anton's most enduring character was Clorox from the "Star Trek: Deep Stain Nine" sketches. Clorox was supposed to be the main nemesis of the sketch and was loosely based on Q from the Star Trek series. Anton left MADtv in 1998, at the end of the season.

Other television projects
Since leaving MADtv, Anton developed an extensive resume on television. He co-starred in several television series, including shows like The Army Show, Random Play, and Primetime Glick. In the late 1990s, Anton guest starred on television series credits included Mr. Show with Bob and David, and Coach. During the 2000s, Anton appeared in shows like Curb Your Enthusiasm, The King of Queens, Ally McBeal, Lizzie McGuire, Everybody Loves Raymond, and Weekends at the D.L. Anton has also appeared on shows like Premium Blend and Late Friday where he performed his stand-up routine.

Television
 Tom Goes to the Mayor (2004) - City council member
 Phil of the Future (2004-2006) - Lloyd Diffy
 The Army Show (1998) - Lt. Branford Handy
 MADtv (1995-1998) - Various characters

Guest appearances
 Entourage (2006) - MC
 Boston Legal (2006) - Ray Richardson
 The Office   (2006) - Craig
 Weekends at the D.L. (2005) - Winston Sicklebee
 Lucky (2003) - Unknown
 Everybody Loves Raymond (2002) - Neil
 The King of Queens (2001-2005) - Mitch/Neal Berger
 Lizzie McGuire (2001) - Mr. Pettus
 Ally McBeal (2001) - Roger Clayton
 Primetime Glick (2001) - Various characters
 Late Friday (2001) - Himself
 Curb Your Enthusiasm (2000) - Craig
 Premium Blend (1997) - Himself
 Coach (1996) - Brian
 Mr. Show with Bob and David (1995) - Expert truck driver

Filmography
 Careless (2007) - Officer Bill
 D-WAR (2005) - Dr. Austin
 The Goldfish (2003) - Duncan Poole
 Deliver Us From Eva (2003) - Theo Wilson
 Live from Baghdad (2002) - American hostage #2
 Run Ronnie Run (2002) - Agent
 Driven to Drink (1998) - Bartender
 Mail Bonding (1995) - Poet

Personal life
In 2006, Craig was living in Los Angeles, California with his wife, Lesley Barr, and their two daughters, Ruby and Delphine. They had an Australian shepherd named Wayne and a cat named Snow White. Craig was doing The Tomorrow Show.

Other websites

1962 births
Living people
American television actors
Comedians from Omaha, Nebraska
Actors from Omaha, Nebraska

Craig Anton


Sumba is an island in Indonesia, and is one of the Lesser Sunda Islands. It has an area of 11,153 km², and the population was at about 611,422 people as of the year 2005. There is a dry season from May to November and a rainy season from December to April. Historically, this island exported sandalwood.

Lesser Sunda Islands

Sumba


Czapka (, ; also spelt chapka or schapska ) is a Polish, Belarusian, and Russian generic word for a cap. However, it is perhaps best known to English speakers as a word for the 19th-century Polish cavalry headgear, consisting of a high, four-pointed cap with regimental insignia on the front (full name in Polish: czapka rogatywka, initially: konfederatka) to which feathers or rosettes were sometimes added.

History

Origins
This headdress developed initially as a square-topped variant of a shako. In its early, compact form from 1784 onwards the czapka was introduced by Austrian uhlans, during the time Galicia was under Habsburg rule. Its use was spread from eastern Europe by the Polish Legion, fighting for the French in the Napoleonic Wars, and became popular not only among Napoleon's French and allied forces, such as Westphalia, Bavaria, Saxony, and Naples, but also among the armies of his enemies. The Duchy of Warsaw used them for infantry and artillery units, but otherwise they were only ever used for uhlan units.

After the Polish lancers proved their effectiveness during the Napoleonic Wars, armies across Europe quickly adopted the concept of the lancer regiments, complete with the czapka as their headdresses.

Nineteenth-century usage

At the end of the Napoleonic Wars the czapka continued to be worn by uhlans in Germany and Austria, as well as in France by Line-Regiment Lancers and later the Imperial Guard of Napoleon III. Lancer regiments in the British Army continued to wear czapkas (described as "lance caps") for full dress until 1939 and the modern Royal Lancers still retains this historic headdress for its Lancer Honour Guard. Along with the traditional double-breasted plastron-fronted lancer jacket, it is also still worn by the band of the Royal Yeomanry.

With the end of the Second French Empire lancer regiments, and thus the czapka, disappeared from the French Army.

The German or Austro-Hungarian czapka ("shapka") consisted of a body of pressed blackened leather, known as the cap and only given a shield on the front. This ended halfway down the back of the head and only protected the front of the head. Instead of a peak, the front was centred on the front point of a four-cornered lid on a stem on top of the helmet. On the left front edge of this lid was attached the National or cockade. There was also a sleeve for the insertion of a brush plume. On the front of the body was a metal emblem (usually an eagle). In German parade examples, a Paraderabatte in the regimental colours was also worn on this type of helmet. In Austro-Hungary they were lined in the regimental colour. A leather chin strap on chains was attached, worn up on the front of the helmet when dismounted. In Austro-Hungary there was also the Kommode-Tschapka, a lighter and more convenient version for field service for officers, without the emblem on the front and with a Wachstuchschicht instead.

The Portuguese cavalry included lancer ("lanceiros") regiments until the overthrow of the Monarchy in 1910, and these retained the czapka in full dress. Spanish lancers wore the "Polish style" headdress from 1833 until after 1868 when a nickel-plated helmet with spike was adopted.

World War I
In 1914 czapkas were still worn in full dress by all Imperial German, Austro-Hungarian, British, Belgian, and Russian lancer (uhlan) regiments. They varied in detail but all had the characteristic four sided top, resembling the mortar-board of academic dress. Plumes were common on parade and in several of the armies named the different regiments were distinguished by the colour of the top or sides. Belgian, Austro-Hungarian, and German lancers wore their czapkas on active service during the opening weeks of the war, usually with dull coloured or waterproof covers. In the case of the Austro-Hungarian Uhlans, since there were not enough of these coverings, many czapka helmets were summarily painted grey. German and Austro-Hungarian uhlans wore the czapka during the First World War, though it ceased to be worn for field uniform after the adoption of the "Stahlhelm" steel helmet in 1916.

Polish usage to present day
During the twentieth century the czapka became one of the symbols of Polish national independence. After World War I, the new Polish Army adopted a four-pointed form as its standard issue national headdress in the form of a rogatywka. After 1952 this czapka style hat was replaced by a round peaked cap of Soviet style, apart from soft field caps, which retained rogatywka style.

In 1982 the rogatywka re-appeared as the headdress of the ceremonial honour guard protecting Belvedere Palace.

Officers of the modern Polish Army wear the four sided cap in certain orders of dress, although berets are the normal headdress.

See also
 Rogatywka

References

Polish cavalry
Military hats

Czapka


Hambleton is a veelage an ceevil parish in Rutland, Ingland.  It is locatit aboot twa mile (3 km) east o Oakham.  In 2001 it haed a population o 140.  Syne the construction o Rutland Water in the 1970s, the veelage haes been closed aff on three sides bi watter an the aurie is kent as the Hambleton Peninsulae.

The parish oreeginally includit the settlements o Upper Hambleton, Middle Hambleton an Nether Hambleton.  The latter twa hae nou been amaist completely submerged bi the construction o Empingham Reservoir (nou Rutland Water). The Jacobean style Auld Haw in Middle Hambleton (biggit in 1611) is nou situatit on the watter's edge.

The veelage contains the 12t century Kirk o Ingland kirk o St Andras, a pub cried The Finch's Arms an a hotel an restaurant, Hambleton Hall. The kirk, hintle enlairged ower its history still haes an oreeginal Norman sooth doorway an wis extensively restored an fittit oot durin the 19t century. This includit excellent stained gless windaes creatit mainly bi J Egan durin the last decade o the 19t century. Adjacent tae the sooth side o the kirk yard staunds a saxteent century priest hoose. The Haw wis biggit in 1881 as a huntin box bi Walter Marshall who left it tae his sister, Eva Astley Paston Cooper. She wis a socialite who gathered a salon includin Noel Coward, Malcolm Sargent an Charles Scott-Moncrieff. Coward wrote Hay Fever while stayin in the veelage.

Thare is a view athort tae Burley House frae the north side o the veelage an frae the sooth ane can see athort tae the sailin club at Edith Weston on the far shore. The track aroond the peninsulae alang the lakeside takes walkers an cyclists throu bluebell woods.

Gallery

References

Freemit airtins

Rutland Wabsteid – Hambleton
Hambleton Veelage History
Hambleton Haw

Veelages in Rutland

Hambleton, Rutland


Duke John II of Bavaria-Munich (1341 – 1397), (German: Johann II, Herzog von Bayern-München), since 1375 Duke of Bavaria-Munich. He was the third son of Stephen II and Elizabeth of Sicily.

Family
His maternal grandparents were Frederick III of Sicily and Eleanor of Anjou. Her parents were Charles II of Naples and Maria Arpad of Hungary.

Maria was a daughter of Stephen V of Hungary and his wife, queen Elisabeth, who was daughter of Zayhan of Kuni, a chief of the Cuman tribe and had been a pagan before her marriage.

Stephen V was a son of Béla IV of Hungary and Maria Laskarina. Maria Laskarina was a daughter of Theodore I Lascaris and Anna Angelina. Anna was a daughter of Eastern Roman Emperor Alexius III and Euphrosyne Doukaina Kamaterina.

Duke of Bavaria
From 1375 to 1392 John ruled in Bavaria-Landshut with his brothers Stephen III and Frederick. In 1385 John II and his wife inherited a third of County of Gorizia with Lienz, but already in 1392 he sold his part to the Habsburgs. In 1392 John initiated a new partition of Bavaria since he refused to finance the Italian adventures of his brothers who were both married with daughters of Bernabò Visconti but also Stephen's expensive holding of court. The duchy of Bavaria-Landshut then was reduced since Bavaria-Ingolstadt and Bavaria-Munich were created. Frederick kept Bavaria-Landshut while Stephen received Bavaria-Ingolstadt which he soon treated as a disadvantage. Therefore, John ruled Bavaria-Munich for three years only until 1395, then he shared his power again with Stephen after an armed conflict between both brothers.

John II was succeeded by his sons Ernest and William III who finally managed to enforce their sole rule over Bavaria-Munich against Stephen III. John is buried in the Frauenkirche in Munich.

Marriage and children
John married in 1372 Catherine of Gorizia, a daughter of Count Meinhard VI of Gorizia and Catharina of Pfannberg. Their children were:
Ernest I of Bavaria-Munich (1373–2 July 1438, Munich)
William III of Bavaria-Munich (1375, Munich–1435, Munich).
Sofia of Bavaria (1376–26 September 1425, Pressburg), married in Prague 2 May 1389 King Wenceslaus.
He also had an illegitimate son, Johann Grünwalder (1393–1452), who was Cardinal and Bishop of Freising.

Ancestors

References

Sources

1341 births
1397 deaths
14th-century dukes of Bavaria
House of Wittelsbach
Burials at Munich Frauenkirche

John II, Duke of Bavaria


The Japan Series ( , officially the Japan Championship Series,  ), also the Nippon Series, is the annual championship series in Nippon Professional Baseball, the top baseball league in Japan. It is a best-of-seven series between the winning clubs of the league's two circuits, the Central League and the Pacific League, and is played in October or November. The first team to win four games is the overall winner and is declared  each year. The Japan Series uses a 2–3–2 format.

The home team for games 1, 2 and eventually 6 and 7, alternates between the two leagues with the Pacific League having the advantage on the years ending with an odd number and the Central League on the years ending with an even number. Designated hitters are used if the team from the Pacific League hosts the game. There is a 40-man postseason roster limit, and the rule on drawn games is changed to 12 innings, since 2018.  If the series is tied after the seventh game, a Game 8 will be held with the same team hosting Games 6 and 7 hosting this game. Only once a Game 8 has been played in Japan Series history, where the Seibu Lions defeated the Hiroshima Toyo Carp in 1986. In the event that Game 8 does not decide the series, the next game would be played at the stadium that hosted Games 3 through 5 after a day of rest, and games will continue until one team wins four games.

Every current team in the NPB has won the Japan Series at least once. The team with the most championships is the Yomiuri Giants, who have won the Japan Series twenty-two times.  In 2004, the Pacific League instituted a three-team stepladder playoff format to determine the league champion, while the Central League champion had a long wait before the Japan Series.  During this time, the Pacific League won four consecutive Series from 2003 to 2006.  Starting with the 2007 postseason, both leagues adopted the Climax Series to determine their champions.  The Climax Series involves the top three finishers in each league, though the format gives a significant advantage to the team with the best record in each league.

On November 6, 2010, the Chunichi Dragons and Chiba Lotte Marines played the longest game in Japan Series history. It lasted fifteen innings and resulted in a 2–2 draw, with the game lasting 5 hours and 43 minutes. Only Game 2 of the 2022 Japan Series on October 23, 2022 came close, with the Orix Buffaloes and Tokyo Yakult Swallows playing to a 3-3 draw after 12 innings, lasting 5 hours and 3 minutes.

Even though the Central League is historically more victorious, in recent years, the Pacific League has been catching up in titles. Currently, Pacific League has 37 Japan Series victories, while Central League has 36. Between 2013 and 2020, Pacific League won the Japan Series 8 times in a row. Six of them were by the Fukuoka SoftBank Hawks, and one each by the Hokkaido Nippon-Ham Fighters and Tohoku Rakuten Golden Eagles. The streak was broken in 2021, with the Tokyo Yakult Swallows beating the Orix Buffaloes.

List of winners

Kazuhisa Inao, as an exception, won the Fighting Spirit Award (in 1956) while playing for the victorious Nishitetsu Lions.

Extra inning rules
With changes introduced as of 2018, the current rules stipulate that the first seven games originally scheduled are called if tied after 12 innings, and if extra games are necessary, the games are played until a victor is decided (unlimited innings), with no curfew limitations.

Historically:
 Until 1966 (except 1964): Game is called at sunset (all games were played as day games)
 1964 (all games at night): No new inning may start after 10:30 p.m.
 1967-1981: No new inning may start after 5:30 p.m.
 1982-1986: No new inning may start after the game time reaches four-and-a-half hours
 1987-1993: 18-inning limit until Game 7, unlimited innings Game 8 and onward (change introduced due to Game 8 being necessary in the 1986 series due to Game 1 being called after 14 innings)
 1994: 18- (day game) / 15-inning (night game) limit until Game 7, unlimited innings Game 8 and onward
 1995-2017: / 15-inning limit until Game 7, unlimited innings Game 8 and onward
 The three-and-a-half hour cut-off rule used in the 2011 regular season was not used for the Japan Series.
 Since 2018: 12-inning limit until Game 7, unlimited innings Game 8 and onward

Teams by number of wins

The franchise currently known as the Saitama Seibu Lions had a Japan Series record of 3–2 as the Nishitetsu Lions.
The franchise currently known as the Fukuoka SoftBank Hawks had a Japan Series record of 2–8 as the Nankai Hawks, and 2-1 as the Fukuoka Daiei Hawks.
The franchise currently known as the Orix Buffaloes had a Japan Series record of 3–7 as the Hankyu Braves, and 1–1 as the Orix BlueWave.  It took its current name in 2005 after merging with the Osaka Kintetsu Buffaloes.
The franchise currently known as the Chiba Lotte Marines had a Japan Series record of 1–0 as the Mainichi Orions, 0–1 as the Daimai Orions, and 1–1 as the Lotte Orions.
The franchise currently known as the Hokkaido Nippon-Ham Fighters had a Japan Series record of 1–0 as the Toei Flyers.
The franchise has a Japan Series record of 1-0 as Yokohama Baystars and a Japan Series record of 1–0 as the Taiyō Whales.
The Osaka Kintetsu Buffaloes were merged with the Orix BlueWave in 2005 to form the Orix Buffaloes.
The Shochiku Robins were merged with the Taiyō Whales in 1953, eventually becoming the Yokohama DeNA BayStars.

Leagues by number of wins

Streaks and droughts
 The Yomiuri Giants won nine consecutive Japan Series championships from 1965 to 1973.  The second-longest streak is four consecutive championships, accomplished by the Fukuoka Hawks from 2017 to 2020. Three consecutive championships have been accomplished by the Yomiuri Giants (1951–1953), the Nishitetsu Lions (1956–1958), the Hankyu Braves (1975–1977), and twice by the Seibu Lions (1986–1988 and 1990–1992).
 The Yomiuri Giants also won five consecutive Central League pennants from 1955 to 1959, and 19 of the 23 Central League pennants from 1951 to 1973.  The Giants also won two consecutive Central League pennants on several other occasions.  The only other teams to win consecutive Central League pennants are the Hiroshima Toyo Carp (1979–1980), the Yakult Swallows (1992–1993), and the Chunichi Dragons twice (2006–2007 and 2010–2011).
 The Nankai Hawks won three consecutive Pacific League pennants twice (1951–1953 and 1964–1966).  The Hankyu Braves won nine of the 12 Pacific League pennants from 1967 to 1978, including three consecutive (1967–1969) and four consecutive (1975–1978).  The Seibu Lions won 11 of the 14 Pacific League pennants from 1985 to 1998, including four consecutive (1985–1988) and five consecutive (1990–1994).
 Franchises have gone 20 years or more without a Japan Series championship over the following intervals:
Osaka Kintetsu Buffaloes,  years (1950–2004, the entire franchise history; the drought extends to 72 years if one includes the history of the merged Orix Buffaloes, who finally won the 2022 Japan Series).
Chunichi Dragons,  years (1955–2006)
Toei Flyers / Nippon-Ham Fighters,  years (1963–2005)
Taiyo Whales / Yokohama BayStars,  years (1961–1997)
Hiroshima Toyo Carp,  years (1985–present)
Hanshin Tigers,  years (1986–present)
Hanshin Tigers,  years (1950–1984)
Nankai/Fukuoka Hawks,  years (1965–1998)
Lotte Orions / Chiba Lotte Marines,  years (1975–2004)
Hiroshima Toyo Carp,  years (1950–1978)
Kokutetsu Swallows / Sankei Atoms / Yakult Swallows,  years (1950–1977)
Hankyu Braves,  years (1950–1974)
Mainichi/Daimai/Tokyo/Lotte Orions,  years (1951–1973)
Nishitetsu Lions / Seibu Lions,  years (1959–1981)
 Franchises have gone 20 years or more without a league pennant over the following intervals:
Taiyo Whales / Yokohama BayStars,  years (1961–1997)
Lotte Orions / Chiba Lotte Marines,  years (1975–2004)
Osaka Kintetsu Buffaloes,  years (1950–1978)
Hiroshima Toyo Carp,  years (1950–1974)
Nankai/Fukuoka Hawks,  years (1974–1998)
Nippon-Ham Fighters,  years (1982–2005)
Hiroshima Toyo Carp,  years (1992–2016)
Hanshin Tigers,  years (1965–1984)

See also

 Nippon Professional Baseball
 Asia Series

References

Baseball competitions in Japan
Recurring sporting events established in 1950

Japan Series


Grand Theft Auto: San Andreas is one of the video games for the Grand Theft Auto game series. It was made by Rockstar Games. The game came out on the PlayStation 2 first and later on Xbox and PC. In this game, the player can do whatever they want, including hitting or killing people, damaging cars and properties and such violent things. That's one reason why the game is so famous. So in the U.S. and Canada it was rated mature (17+) by the ESRB.
The PlayStation 2 version became available on the PlayStation Network for PlayStation 4 on 5 December 2015.

Gameplay
It is set in third-person which means the player can see the person (in this case it is CJ) on the screen. He is controlled using the left and right analog sticks on the PlayStation 2 controller. CJ is the character who is used to play with and he can perform different moves. These are shooting, kicking/punching, jumping, crouching, and even swimming. He can attack other people by either using hand-to-hand combat or shooting them. Sometimes, the attacked person may fight back and try to kill the player. He can get into a nearby vehicle or steal one from another person if it is being driven. If the police see CJ doing crimes, however, they will chase him and try to stop him. If CJ gets caught by the police he loses all of his weapons and some money and he will appear at the nearest police station (the same happens when the player dies, except he appears at a hospital instead). If CJ loses his weapons, he can buy weapons from different gun shops (although he must pay for them).
There are many missions to be taken; the game as a whole has a plot, and the missions the player solves make the plot go on and help the player for his/her abilities (which are for example swimming, condition but also driving bicycles without falling from them and better shooting. Respect is also an important 'ability' players can earn, as they need it to go on in the plot of the game and take more missions), and helps the player to earn money, which can be spent on cars, food (to stop the player from getting hungry), weapons, and a lot of other things. Besides missions, however, the player can also do a number of different challenges, which are not needed for the story but can be used just to help CJ earn some extra money. The game takes place in a fictional state called San Andreas, which has three cities: Los Santos (Los Angeles), San Fierro (San Francisco), and Las Venturas (Las Vegas). Between the cities are also countryside, and the desert of Bone County, based on the real life Nevada desert.

Driving
CJ can drive all sorts of vehicles. He can fly planes, drive cars sail boats and now a jet pack which was not in the previous games. In some vehicles that have hydraulics (where the car 'hops') the analog sticks can be used. If 'nitrous' have been put on (by using a nearby garage) he can drive at incredible speeds which are a lot faster than normal driving. It is also possible to drive around with go-karts or tractors, which was not possible in the previous games; but these vehicles are quite slow and more for fun than for travelling around the map. The player has to be careful, however, not to damage the vehicle too much, because then it might explode, killing or hurting CJ, and causing the vehicle to be useless. Vehicles can also be destroyed by hitting, shooting, setting the vehicle on fire, or driving it into water.

Multiplayer
San Andreas Multiplayer and Multi Theft Auto, often shortened to SA-MP and MTA respectively, are popular multiplayer edits of the original game San Andreas. They have thousands of servers online and runs game servers.

Radio stations
Like previous games in the series, Grand Theft Auto: San Andreas has many radio stations that play songs. The player can listen to these radio stations when in most vehicles, or also from the "options" menu. The radio stations also have DJs and commercials to make them more realistic. There is even a talk radio station, where the player can listen to news within the game and entertainment programs. These radio stations include:

K-DST (Classic rock), Playback FM (Old school Hip-Hop), K-Rose (Country), Bounce FM (Funk), K-Jah West (Reggae and dub), Master Sounds 98.3 (Rare groove, jazz), CSR 103.9 (New Jack Swing), Radio Los Santos (Gangsta Rap), SF-UR (House), and WCTR (News & entertainment).

Plot

Carl "CJ" Johnson comes back to Los Santos, San Andreas in 1992 for his mother's funeral after living in Liberty City for five years since 1987. On his return to the neighborhood, a couple of corrupt cops frame him for the death of a police officer. CJ is forced on a journey that takes him across the entire state of San Andreas, to save his family and to take control of the streets.

References

PlayStation 2 games
PlayStation 3 games
Windows games
Xbox games
Xbox 360 games
2004 video games
Grand Theft Auto

Grand Theft Auto: San Andreas


Elzéar-Alexandre Taschereau (February 17, 1820 – April 12, 1898) was a Canadian Cardinal of the Roman Catholic Church. He served as Archbishop of Quebec from 1871 until his death in 1898. The first Canadian cardinal, he was elevated to the College of Cardinals by Pope Leo XIII in 1886.

Biography
One of seven children, Elzéar-Alexandre Taschereau was born in Sainte-Marie-de-la-Beauce, Quebec, to Jean-Thomas Taschereau and Marie Panet. His father was a judge of the Court of King's Bench of Quebec, and his mother was the daughter of Jean-Antoine Panet, the first Speaker of the Legislative Assembly of Lower Canada. His older brother, Jean-Thomas, was later a Puisne Justice of the Supreme Court. His great-uncle was Bernard-Claude Panet, who also served as Archbishop of Quebec (1825–1833).

Taschereau studied at the Seminary of Quebec from 1828 to 1836, and then traveled for a year to Great Britain, the Low Countries, France, and Italy. While in Rome, he received the tonsure on May 20, 1837, and his friendship with Dom Prosper Guéranger, O.S.B., led him to seriously consider joining the Benedictines. Instead he continued his studies and was ordained a priest for the Archdiocese of Quebec on 10 September 1842.

As a young priest, Taschereau was involved in providing care to the Irish immigrants to Quebec fleeing the Great Famine.  Due to the terrible conditions on the ships bringing the immigrants, typhus was rampant. Taschereau described one ship, the Agnes, as "the most plague-ridden ship of all and in danger of losing everyone on board."  In the end, the Agnes had a death rate of forty per cent.

Taschereau obtained a doctorate in Canon law in Rome in 1856 and had a dual career in teaching and pastoral care. He served as a teacher, director, prefect of studies and Superior at the Seminary where he himself had studied for ordination. He helped found the Université Laval in 1852 and served as its second Rector (1860–66, 1869–71). He remained on the staff of the Seminary until his consecration as the Archbishop of Quebec on 19 March 1871.

At the urging of the Canadian government and many of the faithful, in 1886 Pope Leo XIII made Taschereau Cardinal-Priest of Santa Maria della Vittoria, Rome, the first from Canada. He was not able to stay in his post as archbishop for long, however, as illness forced him to turn over his workload to Mgr. Louis-Nazaire Bégin, who was named as his Coadjutor Archbishop in 1892. Cardinal Taschereau died in Quebec City on April 12, 1898.

References

External links

 Biography at the Dictionary of Canadian Biography Online
 The Cardinals of the Holy Roman Church, by Salvador Miranda at Florida International University
 Biography at the Catholic Encyclopedia
 The Canadian Encyclopedia: Taschereau, Elzéar-Alexandre
 Assemblée Nationale Quebec: Thomas-Pierre-Joseph Taschereau (in French)

1820 births
1898 deaths
Roman Catholic archbishops of Quebec
Canadian cardinals
Cardinals created by Pope Leo XIII
Rectors of Université Laval
People from Beauce, Quebec
Elzear-Alexander
19th-century Roman Catholic archbishops in Canada
Burials at the Cathedral-Basilica of Notre-Dame de Québec

Elzéar-Alexandre Taschereau


Glasgow Coma Scale or GCS is a scale that is used to measure the consciousness of a person. It was invented in 1974 by Graham Teasdale and Bryan J. Jennett, professors of neurosurgery at the University of Glasgow.

GCS is used in evaluation of patients, especially in ICUs. This scale consists of three tests, which are described below. A score is given for each test, and the GCS score is calculated by adding the scores given to each test. The maximum score is 15, which means the patient is fully conscious. The minimum score is 3, and is usually seen in patients with brain death or those in deep coma.

Elements of the scale

The scale comprises three tests: eye, verbal (talking) and motor (movement) responses.

Best eye response (E)
There are 4 grades for this test:
 No eye opening
 Eye opening in response to pain (for example when his sternum is pressed firmly).
 Eye opening to speech (that is, when he is called).
 Eyes opening by himself (normally).

Best verbal response (V)
There are 5 grades for this test:
 No verbal response (not talking at all).
 Meaking meaningless sounds (that is, moaning but no words).
 Inappropriate words (like random speech, without being able to communicate correctly).
 Confused. (The patient responds to questions but there is some confusion).
 Oriented. (Patient responds appropriately to questions such as the patient's name and age, where they are and why, the year, month, etc.).

Best motor response (M)
There are 6 grades for this test:
 No motor response (no movement at all).
 Extension in response to pain (decerebrate response: adduction, internal rotation of shoulder, pronation of forearm).
 Flexion in response to pain (decorticate response).
 Withdrawing from pain (pulling part of body away when pinched).
 Localizing to pain. (Purposeful movements towards the painful location).
 Obeys commands. (The patient does simple things he is asked to do).

References
 Teasdale G, Jennett B. Assessment of coma and impaired consciousness. A practical scale. Lancet 1974,2:81-84. PMID 4136544.

Psychiatry
Medicine

Glasgow Coma Scale


The basking shark (Cetorhinus maximus) is a huge filter-feeding shark, which can grow up to the length of 40 feet (12 metres). It is the second largest shark in the world (after the whale shark). The basking shark is also called the sunfish, the bone shark, the elephant shark, the sailfish shark, and the big mouth shark.

Description

The basking shark is one of the most recognizable species of all sharks. Its large size and extended gill slits which nearly encircle the head and caudal fin together, helps distinguish it from all other species. It has a snout which is in the shape of a cone, and it has many large gill rakers made for filter feeding. Its enormous mouth extends past the small eyes and contains many small, hooked teeth. The basking shark has a very large liver that makes up to 25% of its body weight. The liver is high in squalene, a low-density hydrocarbon that helps the shark float and not sink.
The dorsal surface of the basking shark is mainly a greyish-brown colour, but can range from dark grey to almost black. The underside is usually the same colour, but is often paler and more whiter.
The basking shark has many hundreds of tiny teeth. Those teeth which are in the center of the jaws are low and triangular while those on the sides are more cone-shaped and slightly recurved. There is mainly a wide space on the center of the upper jaw which only has scattered teeth.
The basking shark is the second largest shark in the world, only to be behind the Whale shark. The basking shark can reach lengths of up to 40 feet (12 metres), but the average adult length is 22–29 feet (6.6-8.7 m). The size at birth is believed to be between 5–6 feet (1.5-1.8 metres). The basking shark is an extremely slow-growing species and may grow to 16–20 feet (4.8–6 metres) before becoming mature.

Habitat
The basking shark is a coastal-pelagic species, found throughout the world's arctic and temperate waters. In the western Atlantic, it ranges from Newfoundland to Florida, and southern Brazil to Argentina. In the eastern Atlantic it ranges from Iceland and Norway to Senegal, including the parts of the Mediterranean. In the western Pacific, it is found off Japan, China and the Koreas as well as western and southern Australia and the coastlines of New Zealand. In the eastern Pacific, it is found from the Gulf of Alaska to the Gulf of California and from Ecuador to Chile.

Behaviour
Basking sharks are usually found travelling in pairs or groups of up to 100 or more, but are sometimes seen travelling alone. It is not fully understood why they have such a different behaviour to other shark species, as they seem to travel alone and in groups. They are highly migrational, and in the winter months they will be harder to find as they go to the deeper parts of the water to find food.
When they are seen swimming in circles, it is believed that this is to get the attention of females for mating. They may spend hours performing this, just in order to get noticed. They are usually very patient when it comes to attracting a mate.

Feeding

Along with the Whale shark and the Megamouth shark, the basking shark is one of three species of large, filter-feeding sharks. However, the basking shark is the only one that relies on the flow of water through its pharynx by swimming. The basking shark is usually seen swimming with its mouth wide open, taking in a continuous flow of water. Food is strained from the water by gill rakers in the gill slits. The basking shark's gill rakers can strain up to 2000 tons of water per hour. These sharks feed along areas that contain high densities of large zooplankton (i.e., small crustaceans, invertebrate larvae, and fish eggs and larvae). There is a theory that the basking shark feeds on the surface when plankton is common, then sheds its gill rakers and hibernates in deeper water during winter. Also, it has been suggested that the basking shark turns to benthic (near bottom) feeding when it loses its gill rakers. It is not known how often it sheds these gill rakers or how quickly they are replaced.

Reproduction
Basking sharks are ovoviviparous, meaning that the young embryos develop in a yolk sac inside of the female, but they aren't attached to a placental connection. It is believed that the females can delay gestation so that they may remain pregnant from 1 to 3 years. Mating occurs in the early summer and the females often move to very shallow water when ready for the young to be born. She may have up to 6 pups that are up to 6 feet long. The age of maturity is from 6 to 13 years. Basking sharks start mating when they are around 15 to 20 feet long.

Migration
Basking sharks are highly migratory. Off the Atlantic coast of North America, it appears in the southern part of its range (North Carolina to New York) in the spring, shifts northward (New England and Canada) in the summer, and disappears in autumn and winter. Off the southwest coast of the United Kingdom, in the northeast Atlantic, the basking shark feeds at the surface of coastal waters during the summer. These sharks are absent from November to March, suggesting a migration beyond the continental shelf during the winter months. This is explained by the high amount of zooplankton (the main food of the basking shark) that exists in these waters during late spring and early summer. During migration, basking sharks form groups depending on size and gender.

Parasites
Many people have witnessed individual basking sharks leaping from the water. This behaviour is not fully understood, but some believe that the shark may be trying to get rid of parasites or commensals such as remoras and sea lampreys, which are often seen attached to the skin of the basking shark. The lamprey cannot cut through the denticle-armored skin, but they may be enough of an irritant to cause a reaction like jumping or rubbing against an object to get rid of them. The cookiecutter shark has also been known to attack basking sharks by using its suction cup-like lips and muscular pharynx to drill off pieces of flesh on the outside of the shark.

Conservation
The basking shark has been hunted for its large liver, which has been sold in Japan, and has been burned and used in lamps by fishermen in the U.K, whilst the oil has been used in the manufacture of cosmetics. Due to the long amount of time it takes to mature, and the slow reproductive rate, the basking shark is vulnerable to over-fishing, and targeted populations are very slow to recover from targeted fisheries. Today the biggest threat comes from the demand for the fins for shark fin soup, and from accidental by-catches in the fishing industries. Although it is difficult to tell exactly, there has been a report that the population of basking sharks has decreased by 80% since 1950.

References

Sharks

Basking shark


Luc Bondy (17 July 1948 – 28 November 2015) was a Swiss theatre and film director.

Life and career

Trained in Paris with the theatre teacher Jacques Lecoq, he received a job in 1969 as an assistant at the Hamburg Thalia Theatre. In a surprise, he took over in 1985 after the resignation of Peter Stein at the Schaubühne in Berlin. He also worked as a producer of both plays and operas at the Salzburg Festival, and in 1985 as a director at the Vienna Festival.

He was the director of the most recent version of Tosca, by Puccini, at the Metropolitan Opera in New York. Both the opera, as well as the director, were greeted by loud boos on opening night, 21 September 2009. The reception was generally negative. James Levine, the music director at the Metropolitan Opera likened the production to a 'Hitchcock movie' and the cultural critic for the New York Times, Charles McGrath, felt that the new production was a part of Gelb's mission to transform the Met by emphasizing theatricality.

In an interview after the premiere of Marc-André Dalbavie's opera Charlotte Salomon, Bondy was asked whether his being Jewish had anything to do with his having directed the production. "So I said to her this is a production about a Jewish artist...the subject is the story of Charlotte Salomon" said Bondy, who then walked out on the interviewer.

He died on 28 November 2015 in Zurich.

Direction
Source:

Stage productions
 1971 : Der Narr und die Nonne (The Fool and the Nun) by Stanisław Ignacy Witkiewicz at Göttingen
 1973 : Die See (The Sea) by Edward Bond at the Munich Residenztheater
 1974 : Glaube, Liebe, Hoffnung (Faith, Love, Hope) by Ödön von Horvath at Hamburg
 1977 : Man spielt nicht mit der Liebe by Alfred de Musset at the Schaubühne, Berlin
 1980 : Happy Days by Samuel Beckett at Cologne
 1980 : Yvonne, die Burgunderprinzessin (Yvonne, the Princess of Burgundy) by Witold Gombrowicz at Cologne
 1982 : Macbeth by William Shakespeare at Cologne
 1983 : Sommer (Summer)  by Edward Bond at Munich
 1984 : Das weite Land (The Far Country) by Arthur Schnitzler at the Théâtre des Amandiers in Nanterre
 1985 : Triumph der Liebe (The Triumph of Love) by Marivaux
 1989 : Le conte d'hiver by Shakespeare, at Nanterre-Amandier
 1989 : Die Zeit und das Zimmer (The Time and the Room) by Botho Strauß, at Berlin (premiere)
 1990 : The Winter's Tale by Shakespeare, at the Lehniner Palace
 1992 : Schlußchor by Botho Strauß at Berlin (premiere)
 1993 : John Gabriel Borkman by Henrik Ibsen at the Théâtre de l'Odéon, Paris
 1993 : Das Gleichgewicht (The Equilibrium) by Botho Strauß, at the Salzburg Festival (premiere)
 1994 : Die Stunde da wir nichts voneinander wußten by Peter Handke
 1999 : Waiting for Godot by Samuel Beckett, at the Vienna Festival
 2000 : Drei Mal Leben by Yasmina Reza, at the Burgtheater in Vienna (premiere)
 2002 : Anatol by Arthur Schnitzler, at the Burgtheater in Vienna
 2004 : Cruel & Tender by Martin Crimp, at Young Vic, London (premiere)
 2005 : Die eine und die andere by Botho Strauß, at Berlin
 2005 : Viol by Botho Strauß, after Titus Andronicus, at Odéon, Atelier Berthier, Paris
 2010 : Sweet Nothings by David Harrower from Arthur Schnitzler's Liebelei at Young Vic, London (premiere)

Opera productions
 1986: Così fan tutte by Mozart (conducted by Sylvain Cambreling), at Amandier, La Monnaie, Wiener Festwochen
 1989: L'incoronazione di Poppea by Monteverdi, revised Philippe Boesmans, at Amandier, La Monnaie
 1990/1: Don Giovanni by Mozart (conducted by Claudio Abbado, starring Ruggero Raimondi), at Wiener Festwochen
 1992: Salome by Richard Strauss (conducted by Christoph von Dohnányi, starring Catherine Malfitano and Anja Silja), at the Salzburg Festival, Royal Opera House
 1993: Reigen by Philippe Boesmans (libretto by Luc Bondy, after "La ronde" by Schnitzler) at La Monnaie
 1995: Le nozze di Figaro by Mozart (conducted by Nikolaus Harnoncourt), at the Salzburg Festival
 1996: Don Carlos by Giuseppe Verdi (conducted by Antonio Pappano, starring Roberto Alagna, José van Dam, Karita Mattila), at Châtelet, Royal Opera House, Opéra de Lyon, Edinburgh Festival
 1999: Wintermärchen by Philippe Boesmans (libretto by Luc Bondy, after The Winter's Tale by Shakespeare), at La Monnaie
 2000: Macbeth by Giuseppe Verdi (conducted Richard Armstrong), at Wiener Festwochen, Scottish Opera
 2001: The Turn of the Screw by Benjamin Britten (conducted by Daniel Harding), at Festival d'Aix-en-Provence (reprise 2005)
 2003: Hercules by Handel (conducted by William Christie with Les Arts Florissants) at Festival d'Aix-en-Provence, Opéra National de Paris, Wiener Festwochen, De Nederlandse Opera
 2005: Julie by Philippe Boesmans (libretto by Luc Bondy, after Miss Julie by Strindberg), at La Monnaie, Festival d'Aix-en-Provence
 2005: Idomeneo by Mozart (conducted by Daniel Harding), at Teatro alla Scala, Opéra National de Paris (2006)
 2009: Tosca by Puccini (conducted by James Levine), at the Metropolitan Opera, New York City (2009); seen later in Munich and Milan
 2009: libretto for Yvonne, princesse de Bourgogne
 2014: Charlotte Salomon (conducted by Marc-André Dalbavie), at the Salzburg Festival, 2014

Honors
 1984 Deutscher Kritikerpreis, Theater
 1990 Grand Prix Dominique de la mise en scène
 1992 Inszenierung des Jahres, Theater heute, for Schlusschor
 1997 Hans-Reinhart-Ring
 1998 Theaterpreis der Stiftung Preußische Seehandlung
 2000 Nestroy Theatre Prize 2000, Best Director, for Die Möwe The Seagull
 2001 Stanislawskij-Preis in Moskau for Die Möwe''
 2008 Zürcher Festspielpreis für La seconde surprise de l'amour
 2009 Preis der Kythera-Kulturstiftung Düsseldorf
 2013 Goldenes Ehrenzeichen für Verdienste um das Land Wien
 2014 Prix de l'Académie de Berlin

References

External links

1948 births
2015 deaths
Swiss opera directors
Swiss theatre directors
German-language film directors
Swiss film directors
Swiss Jews
Members of the Academy of Arts, Berlin
Film people from Zürich

Luc Bondy