Flexibility, security, scalability, speed, collaboration and data management are key to advance precision medicine. Dr. Frank Lee will introduce a visionary market leader, who will share with you how they revolutionized their capabilities with a high performance data and AI platform as a catalyst that supports data-driven research and accelerates breakthrough discoveries. Come discover how to transform the future of life sciences and precision medicine - now.
RStudio will be presenting an overview of R for deep learning with Tensorflow for the R user community at Bio-IT World 2019. This is a great opportunity to learn and get inspired by new capabilities for applying deep learning techniques used by practitioners for research and scientific computing/tasks.
Traditionally, data analysis in clinical research has been a time-consuming and manual process, and the increasing volume of available data is making it more challenging to derive insights in a precise and timely manner. Bringing together our domain expertise, real-world evidence and high-quality proprietary datasets our tailored approach to developing descriptive and predictive analytical solutions helps customers gain insights faster and make better decisions.
A technical demonstration of how to use the GOR Database (GORdb) to query genomic and phenotypic data across multiple biobanks. Using the R software development kit for GORdb, bioinformaticians can easily interrogate genomic data using a unified schema and query language from their favorite programming language. During this talk, these tools will be utilized to build a cross-biobank group of affected Epilepsy cases using samples from Simons Foundation and UK Biobank.
Efficiently managing and preserving data is essential for pharma and life sciences organizations. As data volume and variety grows, managing and extracting value from it becomes increasingly difficult. Understanding your data is as vital as DNA is to cells. Join us to learn how advanced metadata scraping and powerful queries maximize value and address cost challenges of hot-cold data management.