Title of Invention: Rigorous method and apparatuses for the analysis of complex mixtures of organic molecules with an enhanced degree of information extraction Abstract: Disclosed are a rigorous method and apparatuses for the comprehensive analysis of complex mixtures of organic molecules, specifically biopolymers, in some embodiments predominantly mixtures of proteins, which in some embodiments ultimately serve to obtain the information constituting a biomarker, or similar biological signature, or to monitor health or ageing. In some embodiments such signatures or patterns may indicate the presence, stage, or type of a disease, the expected or actual response to drugs. In some other embodiments such a method and apparatuses may serve to monitor and/or control cell development. In some other embodiments such a method and apparatuses may serve to develop and use means to measure, influence, or control the speed or degree of aging of cells or organisms. In some embodiments such a method and apparatuses may serve to determine at least in part the nature of biological hazards, bioterrorism threats, or biological weapons, including those based on bacteria and viruses. In some embodiments such a method and apparatuses may serve to select, develop, and or optimize countermeasures to biological hazards, bioterrorism threats, or biological weapons, including those based on bacteria and viruses. In other embodiments such a method and apparatuses may be used to asses the expected performance level of a human or animal for a specific task or for a class or problems. Detailed Description: INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57. In particular, this application claims the benefit of U.S. provisional patent application No. 62/307470 filed Mar. 12, 2016, the disclosure of which is incoporated herein by reference. BACKGROUND OF THE INVENTION Field of the Invention Much financial effort and attention has been given to achieving relatively inexpensive and rapid DNA sequencing, specifically also of human DNA, in many cases with hopes of ultimately making clinical use of such technology. The first attempt to obtain a human reference genome was an effort of more than a decade (1990 to 2003) and is estimated to have required about $3 billion in government funding. (A similar, although less costly and less comprehensive, privately funded effort was performed simultaneously.) Due to massive investments, remarkable progress in instrumentation has been achieved during the last 15 years, which has resulted in an exponential decrease in costs and increase in speed thanks to fully automated high-throughput DNA sequencing machines. At the beginning of 2014 Illumina introduced the ‘HiSeq X Ten Sequencer’ which can, on average (if using 10 machines in parallel), sequence entire human genomes for less than $1,000 and in about half an hour. While without any doubt inexpensive DNA sequencing will be of great practical importance for future medical and biological research, many of the original hopes to clinically use genetic information (by itself) for short and medium term health predictions have thus far only partially been fulfilled and are likely to remain illusive for principle reasons in many cases. It is from a theoretical standpoint clear that the missing information is (thus far) hidden in protein abundance levels as well as in chemical modifications on proteins (posttranslational modifications). The challenge when analyzing protein mixtures obtained from nature is twofold: complexity and dynamic range. In addition, the changes in abundance and composition of proteins during the life of an organism are far more dynamic compared to changes of DNA. Due to the enormous complexity of human proteins (several millions) and their huge dynamic range (at least 10 orders of magnitude in human blood) protein mixture analysis represents an extraordinarily complicated metrology problem. After the introduction of high throughput DNA sequencing, the next technologically feasible long term goal, likely achievable within less than a decade, must now be a comprehensive “$1000 human protein profile” based on orders of magnitude faster and intrinsically quantitative (label free) instruments to analyze complex protein mixtures. In some embodiments the disclosed invention provides elements to at least approach or even realize this and other goals. To illustrate the transformative impact of groundbreaking inventions a few historic examples shall be given henceforth. The history of science and technology is filled with examples where a substantial increase in performance of a measuring instrument, or a machine (incl. weapons) subsequently enabled fundamental discoveries, caused the transformation of entire industries, opened up entirely new commercial fields, or helped win wars. One of the contributing reasons why Great Britain became a dominating world power in the 18th century was that ships of the British Navy had superior navigation capabilities compared to ships from other navies. They possessed marine chronometers, built by the carpenter John Harrison, which incorporated various motion and temperature compensation methods and which could therefore measure time with orders of magnitude higher accuracy than conventional clocks. The collaboration between Ernst Abbe (providing an improved theory behind optical image formation, as well as novel lens designs such as apochromats), Carl Zeiss, and later Otto Schott (developing borosilicate crown glass with low optical dispersion), ultimately resulted in the design and production of reliable oil immersion microscopes, which operated close to the theoretical optical resolution limit. These instruments enabled numerous discoveries related to microbiology and infectious diseases, including Robert Koch's discovery of the tuberculosis bacterium in 1882. Frits Zernike's invention the (optical) phase contrast microscope (Zernike, 1934, Nobel Lecture 1953) enabled the optical visualization of the internal structure of cells with largely improved contrast while avoiding usually lethal staining, which ushered in the area of research on living cells under microscopic observation. During the early phases of the development of electron microscopes (incl. TEM, SEM, and STEM) during the 1930's and early 1940's (with major contributions by Hiller, Knoll, Ruska, Scherzer, Prebus, v. Borris, v. Ardenne, and others) serious skepticism existed if—although theoretically expected—images with significantly higher than optical resolution could practically be obtained. In Ernst Ruska's own words this was in fact considered “a pipe dream” by most experts at the time (Ruska, Nobel lecture 1986). Nevertheless, this lofty goal was of great interest, since some of the driving motivations behind these efforts, besides emanating from material sciences, came from biology, namely the desire to image viruses and bacteria. Moreover, there were fundamental doubts if biological samples could ever be imaged with electron beams and in vacuum. Nevertheless, in 1934 Ladislas Morton succeeded in obtaining very crude (and still with less then optical resolution) images of a leaf sample. A considerably improved electron microscope, with at least an order of magnitude higher than optical resolution, enabled later to image viruses (at the time still somewhat “mysterious contagious entities”) as well as several bacteria, incl. the tuberculosis bacterium. After the corrective optics was installed in 1993, the Hubble Space Telescope provided images without aberrations introduced by earth' atmosphere and with a quality unmatched by ground-based telescopes at the time (prior to adaptive optics), with much reduced background levels, sensitivity at all wavelengths, hight pointing stability, and wider field-of-view, which enabled numerous astronomical discoveries and improved our understanding of the universe. Godfrey Hounsfield's first laboratory prototype of a X-ray CAT scanner, a tabletop-sized, rather crude and odd looking contraption to the naive observer, produced an image of a (preserved) human brain, which appeared to resemble a card from a Rorschach test instead of a CAT scan—yet it proved the fundamental physical principle (Hounsfield, Nobel lecture 1979). The first CAT scans of (live) human brains obtained 1972 at the Atkinson Morley hospital in London had such high noise levels and low spatial resolution that they had very limited clinical use. One of the original goals of this work was to detect, i.e., “see” (large) brain tumors against healthy brain tissue. Initially it was anything but clear if the required image quality in terms of signal-to-noise ratio, contrast, and resolution could ultimately be achieved. It took another decade to reach full clinical utility. It is in hindsight remarkable that during the late 70's and 80's the development of this technology received sufficient funding to move from a Nobelprize-winning curiosity to a $10B industry today (for hardware alone). All these problems were relatively easy to comprehend since they were essentially confined to a single domain (physics, mechanics, optics), i.e., inventors and instrument/machine builders and “early adopters” had similar technical and scientific backgrounds, thus understood the implications quickly. Nevertheless, many of the aforementioned breakthroughs as well as other inventions had “a difficult birth”. However, at the beginning of the 21tst century we are beginning to see the emergence of a number of multi-disciplinary problems and technical challenges, where it is not instantly clear why progress has heretofore been slow. This is in particular the case for challenges related to the understanding of life, human health, molecular diagnostics, artificial intelligence, and even robotics. All these areas require knowledge in several areas including at least physics, electronics, optics, chemistry, biochemistry, medicine, neurology, computer science, and statistics. One such example is the better understanding of life on a molecular level, in particular the understanding (and utilization thereof in clinically usable methods and devices) of the interplay of DNA (RNA) and proteins as well as the required instrumentation to perform measurements to gain such knowledge. Description of the Related Art Modern DNA sequencing techniques require Polymerase Chain Reaction (PCR), i.e., the ability to chemically multiply (“amplify”) DNA (Mullis, Nobel lecture 1993). Only very recently have single-molecule sequencing machines become commercially available, which are not based on chemical amplification but on extremely sensitive physical detection methods (thanks to the fact that one can count individual photons). These machines represent a physical solution to a biochemical problem, but still only on the level of DNA. Regardless which sequencing technology will eventually commercially prevail, few outsiders are aware of the limitations inherent in the analysis of DNA (and RNA). While clearly many highly interesting insights will be gained from inexpensive widespread DNA sequencing in future years, in particular related to molecular and evolutionary biology as well as the general probability (but not certainty) of an individual to eventually suffer from a certain disease. In fact, even this goal appears to be much more difficult to reach than anticipated since the search for such DNA based markers (i.e., direct links between DNA variants and the tendency to get a disease) has yielded surprisingly few results with sufficiently strong correlation (Hall, 2010, “Revolution Postponed”). Thus, the clinical application of DNA sequencing to medium term health problems is for very principle biochemical reasons limited if not questionable. Even if available, such probability statements based on detected DNA mutation can bring patients in a serious dilemma, having to decide if one should undergo (potentially unnecessary) preventive surgery. A recent example involving a prominent actress has been widely publicized. Of much higher value would be the ability to detect the actually onset of a serious disease, or being able to predict the response to a drug, or to monitor in real time the response to a drug, and/or to choose or modify the composition of a drug in real time a based on measured data. Life is largely based on protein chemistry. According to our current, likely incomplete understanding a 2% fraction of human DNA encodes for only about 22,000 proteins, although this number is still debated. Despite this seemingly small number, it is believed that the human body contains actually several millions of different versions of these proteins due to a) mRNA splice variants, and b) various reversible or irreversible chemical modifications (posttranslational modifications, PTMs) on proteins, which are critical for a person's health. The exact number is not (yet) known for the metrological reasons given below. It is only through a better understanding of gene expression (i.e., protein biosynthesis via molecular transcription and translation), and of the protein networks, that deeper insights and ultimately truly predictive capabilities of human health and drug effectiveness can be potentially achieved. Mammalian cells produce over 1000 proteins (transcription factors, cofactors, and chromatin regulators), which play a role in gene expression, i.e., when and how much of other proteins are produced in the body (based on information residing in DNA), and if the process is performed without errors, yet our understanding of the involved processes and their dynamics is incomplete. Of particular importance in this context are, for example, histones and histone modifications. Thus, it is more accurate to imagine life as a dynamic interplay between DNA, RNA, and protein networks. The abundance and composition of proteins in an organism (“intentionally” as well as due to errors in transcription and/or translation) is far more dynamic compared to changes of DNA during replication. Errors in biological information transfer from DNA to DNA (during cell division), and from DNA to proteins (via RNA) occur in cascades and at different time scales and with largely different probabilities. If we ignore here extreme circumstances such as radiation exposure, the changes that DNA undergoes in an organism are orders of magnitude lower than those of proteins. It has been estimated that the error rates of DNA synthesis are about 10−10 to 10−8 (base pair mutations and frame shifts), of RNA synthesis on the order of 10−5, and of protein synthesis between 10−4 to 10−3. Notably, DNA replications utilizes a form of molecular proofreading and an error correction or “enzymatic editing” mechanism, without which DNA synthesis error rates would be on the order of 10−5 to 10−4 (which would make complex life forms effectively impossible). The correct function of this error correction mechanism, in turn performed by several proteins (e.g. ATR, Exo1, MutS, Msh2-Msh6, XPA, etc.), is thus essential for DNA synthesis. An interesting side aspect is the required technology to quantify such low rates and to detect ultra-rare DNA mutations. Thus, the rates at which DNA modifications occur are several orders of magnitude lower than changes in (and on) proteins. Beside the impact of disordered proteins on cell-signaling, which may also eventually cause and/or indicate various diseases, of great practical importance are (accidental) changes in sequence, changes in abundance, and chemical modifications on proteins (PTMs). Beside errors during protein synthesis, proteins are constantly subjected to degenerative chemical influences, which can result e.g. in oxidation, glycoxidation, phosphorylation, deamidation, or other damages and modifications, and few repair mechanisms on proteins have thus far emerged. It is now in principle clearly understood that such chemical modification on proteins are associated with numerous disorders and diseases (e.g. Alzheimer's, Parkionson's, Huntington's, dementia, immune system diseases such as arthritis, cancer, and many more), since they affect countless pathways (including gene expression itself), but our knowledge of specific correlations is far from complete. Furthermore, cells build proteins at a considerable dynamic range, and many particularly important proteins, such as transcription factors, occur at relatively low abundance. As a result, our understanding of gene expression through transcription and translation has come predominantly from studies conducted on purified molecules from large cell populations, which can obscure several aspects of this inherently “single molecule process”. While specific binding events can be detected on a single molecule level in individual cells, for example with optical detection, comprehensive analysis of protein expression at a single cell level (based on mass spectrometry as explained in more detail later) remains a highly desirable, but thus fare elusive goal, as discussed in more detail later. The dynamic nature of proteins is furthermore illustrated by the concept of an “epigenetic landscape”, a term already coined in 1942 by Conrad Waddington. It is meant as a conceptual analog to illustrate the generally irreversible “decisions” a cell makes along its “trajectory” of molecular development (Goldberg, 2007). In the most general sense, epigenetics concerns the relationship between genotype and phenotype, i.e. how from the same DNA base pair sequence different protein expression level derive. As such, cell differentiation is at least in some respects an epigenetic process. A related concept is “phenotypic noise”. In particular, epigenetic research concerns covalent and non-covalent modifications on DNA and on certain proteins, particularly on histones, and how such changes influence the function of chromatin. Since it is now believed that epigenetic changes are associated with several diseases, incl. at least some cancers, epigenetic mechanisms are now already being considered for therapeutic approaches. Again, the ultimate clinical application of such approaches will (also) depend on a better understanding of epigenetic regulators, including PTMs on certain proteins, which will require at least in part elements of the disclosed invention. Thus, there is a heretofore unfulfilled need for innovation. It is from a theoretical standpoint clearly understandable that the missing information is (thus far) hidden in protein abundance levels as well as in chemical modifications on proteins—posttranslational modifications—(and in some cases in part also in chemical modification on DNA/RNA. As already mentioned, the challenge when analyzing protein mixtures obtained from nature is twofold: complexity and dynamic range. The dynamic range of proteins in bacteria is on the order of 105, in human cells on the order of 107 to 108, and about 1012 in human plasma (Anderson, 2002). In human plasma the 22 most abundant proteins account for about 99% of the protein mass (with serum albumin at≈45mg/ml) while information-carrying proteins incl. tissue leakage products, interleukins, cytokines etc. may occur at 1 . . . 10 pmol/ml (Anderson, 2002). Due to the enormous complexity of human proteins (several millions) and their huge dynamic range, protein mixture analysis represents an extraordinarily complicated metrology problem. Thus, the comprehensive determination of the composition of very complex protein mixtures, i.e., to measure how much and which proteins (including those with chemical modifications) are present in a sample, is the thus far unmet underlying technical requirement. This technical capability is the key to finding clinically usable protein biomarkers, from which various diagnostic tests e.g. for the onset, stage, or type of a specific disease, or for the expected or actual response to an administered drug can be derived. As mentioned above, and to provide a historical analogy, one of the original motivations and goals behind the developments of X-ray scanners in the 1970's was to detect, i.e., “see” (large) brain tumors against healthy brain tissue. Initially it was anything but clear if the required image quality—today taken for granted—in terms of signal-to-noise ratio, contrast, and resolution could ultimately be achieved. In fact, the first CAT scans of (live) human brains obtained 1972 at the Atkinson Morley hospital in London had such high noise levels and low spatial resolution that they had very limited clinical use (Hounsfield, Nobel lecture 1979). Like in the 70's during the development of CAT scanners, one of the goals of analyzing complex protein mixtures is to detect for example cancer at very early stage. But not as an image, rather by sensing molecules either directly in malignant cells taken during a biopsy, or molecules leaked from malignant cells into the blood stream, or molecules contained in malignant cells, which were released from a tumor and are circulating in blood. More precisely, by detecting minute abundance changes and chemical modifications on some proteins or peptides present in cells or in serum due to such leakage. The molecular pattern one is looking for is referred to as protein biomarker. However, despite the great potential, of such multi-parameter protein cancer biomarkers have not yet found their way into routine clinical application. Similarly, highly specific protein biomarkers would be instrumental as companion tests for certain drugs, which are only effective in a portion of the population and/or under certain condition. Without such tests, these drugs would never be approved for general use. As a result, for more than a decade now, enormous efforts and substantial government and private funding (several billion dollars) were invested in attempts to find verifiable, highly specific and sensitive, clinically applicable protein biomarkers and to establish protein biomarker-based clinical diagnostics (Ahrens, 2010). The results are abysmal. A 2010 paper in Nature Biotechnolgy (Mitchell, 2010) brought the scope of the disaster to the attention of the scientific community: “By and large, the search for protein biomarkers—proteins that can indicate the presence of disease or how an individual is responding to therapy—has failed. Considering the hundreds of billions of dollars poured into proteomics research in the past decade, it is striking that not a single commercial molecule has emerged from it.” A similar article in Science “Digging for biomarker gold” summarized the problem as well (Harding, 2012). Likewise, an excellent BMC Medicine paper “The failure of protein cancer biomarkers to reach the clinic . . . ” points out various shortcomings associated with the clinical use of current insufficiently performing protein biomarkers (Diamandis, 2012). In contrast to the disclosed invention, such early attempts of finding protein biomarkers used methods and shortcuts, which have at least in some cases hugely underestimated the vast gap between instrument performance and the demands posed by the complexity and dynamic range of serum, other bodily fluids, or even tissue samples (e.g. using a simple matrix assisted laser desorption ionization (MALDI) single MS linear time-of-flight (TOF) instrument and unfractionated or minimally fractionated serum samples). Thus, the required technical effort was misjudged or ignored. (By way of analogy, the resolution of the first electron microscopes built in the '30s and '40s were orders of magnitude too low to achieve atomic resolution. Any attempts to use these early microscopes e. g. to image crystallographic structures would have been bound to fail.) Nevertheless, it is undisputed that the required information, i.e., highly specific and sensitive biomarkers, must reside in the protein expression levels (incl. potential PTMs). The technical challenge lies in obtaining the required information. It shall also be remarked that thus far attempts using mRNA arrays (and to then infer protein abundance) have proven to yield also few if any useful results, since (a) mRNA levels correlate only weakly with protein expression levels and (b) PTMs of proteins can in principle not be detected this way. Thus the direct detection and quantification of proteins is required. SUMMARY OF THE INVENTION For purposes of summarizing the invention and the advantages achieved over the prior art, certain objects and advantages of the invention are described herein. Of course, it is to be understood that not necessarily all such objects or advantages may be achieved in accordance with any particular embodiment of the invention. Thus, for example, those skilled in the art will recognize that the invention may be embodied or carried out in a manner that achieves or optimizes one advantage or group of advantages as taught herein without necessarily achieving other objects or advantages as may be taught or suggested herein. Disclosed are a rigorous method and apparatuses for the comprehensive analysis of complex mixtures of organic molecules, specifically biopolymers, in some embodiments predominantly mixtures of proteins, which in some embodiments ultimately serve to obtain the information constituting a biomarker, or similar biological signature, or to monitor health and ageing. In some embodiments such signatures or patterns may indicate the presence, stage, or type of a disease, the expected or actual response to drugs. In some other embodiments such a method and apparatuses may serve to monitor and/or control cell development. In some other embodiments such a method and apparatuses may serve to develop and use means to measure, influence, or control the speed or degree of aging of cells or organisms. In some other embodiments such a method and apparatuses may serve to determine at least in part the nature of biological hazards, bioterrorism threats, or biological weapons, including those based on bacteria and viruses. In some other embodiments such a method and apparatuses may serve to select, develop, and or optimize countermeasures to biological hazards, bioterrorism threats, or biological weapons, including those based on bacteria and viruses. In some embodiments the disclosed invention provides a method and apparatuses for the analysis of complex mixtures of predominantly biological molecules (incl. e.g. blood, saliva, sweat, sperm, cell(s), or samples derived there form) with respect to their protein content, the separation and fractionation of which in typically a plurality of dimension (of at least physical and/or chemical and/or biological properties) to enable at least one subsequent analytical method (in some embodiments comprising mass spectrometry), which determines with heretofore unrealized fidelity and degree of completeness (including exhaustively) the composition of said proteins in said mix or sample, in terms of which kind proteins (amino acid sequences) are present, as well as any previously known or unknown chemical modification thereon (including but not limited to what is currently referred as PTMs), present in biological regularly (“healthy”) or irregularly (“diseased”) functioning organism(s) or cell(s), and/or at least partially caused by intended or unintended exposure to or application of any form of treatment(s), drugs, any kind of conditioning, life style(s), work condition(s), or caused by ageing, cosmetics and/or other beauty products, medical procedures, surgical or other operations, predominantly physical processes, exposure to physical effects including but not limited to radiation, fields, pressure, furthermore exposure to or other intake of chemicals other than drugs, including but not limited to chemical additives in products, endocrine disruptors, air pollution, poisons, biological or chemical weapons, furthermore physical exercise, sport, sleep/rest, nutrition (incl. natural, processed, or man made), incl. contamination in or composition of food, or by coincidental or random effects (also in combination), any such said exposure, treatment, or influence, being known or unknown today, and furthermore in some embodiments also how many of each kind of protein (abundance) including how many (abundance) for each type of chemical modification. All of these embodiments are intended to be within the scope of the invention herein disclosed. These and other embodiments of the present invention will become readily apparent to those skilled in the art from the following detailed description of the preferred embodiments having reference to the attached figures, the invention not being limited to any particular preferred embodiment(s) disclosed. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 illustrates highly schematically the process steps of the disclosed method. A raw sample 101, which may in some embodiments be derived e.g. from blood, saliva, other bodily fluids, tissue, cells, or otherwise, is optionally subjected to a preprocessing step 102, which may in some embodiments include, cleaning, filtering, freezing, thawing, extraction of cell content, removal or suppression of undesirable or meaningless (in the context of the specific investigation) content, addition of chemicals, or any other similar methods. The resulting primary sample 103, containing at least a complex mixtures of organic molecules, usually biopolymers, and specifically in some embodiments protein mixtures, is henceforth referred to as the first plurality of sample molecules. In a first process step 104 this first plurality of molecules is subjected to in general a multidimensional (in terms of chemical or physical properties) separation process. FIG. 1 illustrates an example wherein at least partially a 4-dimensional separation occurs, conducted in two consecutive steps 105 and 106, each of which separates at least partially in 2 dimensions predominantly simultaneously. The 4-dimensional parameter space is defined by parameters X1, X2, X3, and X4. First, the [X1,X2] sub-space is scanned, and then in [X3,X4] sub-space. The latter is repeated several times and may be conducted e.g. for a plurality of points (“areas”, “subspaces”) in the [X1,X2] space; in some embodiments these scans are equidistant in the parameter space, and/or nonlinear, and/or discrete, and yet other only selected areas are picked. Thus, in the shown example, the first scan produces a (discrete) two-dimensional plurality of samples 107, and the second scan produces a (discrete) four-dimensional plurality of samples 108. (This is illustrated here for simplicity as the most trivial case with two “data points” in each additional dimension X3 and X4, thus producing roughly four times the number of samples in plurality 108 compared to plurality 107. However, realistically each additional dimension may multiply the number of samples of the output plurality by a factor which may in some cases range from a few to a few hundred in order to achieve the required degree of separation.) The individual samples contained in plurality 108 shall also be referred to as fractions. As the next, second process step 109 at least one, but typically a plurality of physical and/or chemical molecular fragmentation steps are independently, put possible in parallel, performed, which break the biopolymers, specifically relatively large ones, in a controlled fashion into smaller pieces. First, the plurality 108 is at least partially divided in to several pluralities, here labeled 110, and an unspecified number of additional aliquots up to those labeled 111. The molecular fragmentation is in many embodiments done in a manner, whereby this process is selective to sequence information of biopolymers. Illustrated are molecular fragmentation sub-step “MF13 1” 112 and an unspecified number of additional molecular fragmentation sub-steps up to “MF_n” 113. In many embodiments alternate fragmentation methods produce alternate fragments of the same biopolymer. However, at this stage the fragmentation methods do predominantly not break the biopolymers down to monomer level, they typically only reduce the molecular size (weight) to a range, which can at least in part be handled by the subsequent analytical process. Said controlled fragmentation is performed independently (but typically in parallel) for each individual sample (i.e. for each members of pluralities 110 and 111), often contained in individual vials, wells, microtubes, or other cavities in large arrays etc. Thus, the number of input sample and output samples is approximately the same for each molecular fragmentation step. The result, the second process generates third plurality of samples (114 and 115), the size of which depends on the size of plurality 108 (110 and 111 respectively, although the may each be smaller than 108), and the number of molecular fragmentation methods MF_n. At least some members of said third plurality of samples (114 and 115), sometimes most if not all, are then subjected to a third process step 116. This is conducted for each member independently, but possibly in parallel on similar machines. The now at least partially fragmented sample molecules are released in sub-step 117 either directly from predominantly a liquid, and/or in other embodiments they are first transferred to a predominantly liquid crystal, gel-like, or state solid state and then desorbed or otherwise released. In many embodiments the latter is the case, since it helps to spatially and temporally decouple the previous steps from the following. Specifically, in some such embodiments addition molecules are added which may least in part support the process of desorption, protect sample molecules during desorption, and/or at least in part support or selectively support ionization. The released sample molecules and/or fragments thereof are then ionized (although the release from the liquid or solid phase may occur in physical proximity and/or the same device or component of a device. This is in many embodiments a dedicated high performance ion source 118 for biological molecules. In some embodiments such an ion source may also employ additional free charge injection 119 to enhance ionization efficiency, enhance quantitative performance, and increase speed compared to conventional electrospray (ESI) and matrix assisted laser desorption/ionization (MALDI) ion sources. In some embodiments the charge injection also severs to produce sample ions with a specific, selected charge state. In a subsequent fourth process step 120 said ionized molecules are then in some embodiments subjected to an additional separation process. Here illustrated is another tow-dimensional process 121, which selects based on two additional properties. In some embodiments this may include ion collision cross section, symmetry, ion mobility, charge state, mass-to-charge ratio, dipole or higher moments, trajectory stability, or other physical properties, but in many embodiments related to the fact that sample molecules are at that point already ionized. In some cases this may include at least partially trapping said ions in suitable electric and/or magnetic fields. Subsequently said ions are subjected to an analytical process, which determines at least one characteristic quantity of said ionized molecules, which is ultimately suitable to deduce at least the chemical composition of said ionized molecules, in many embodiments this will a the molecular charge-to-mass ratio, or molecular mass. Illustrated is such a first mass spectroscopic stage 122. As pointed out in more detail further down, each (group) of molecular ions (of identical chemical composition) will produce a relatively wide comb-like pattern of peaks due to the distribution of naturally occurring isotopes, primarily 1H, 2H, 12C, 13C, 14N, 15N, 16O, 17O, 18O and others. For typical peptide masses the (only) monoisotopic peak is followed by several, sometimes 5 to 10 depending on the SNR of the spectrum and chemical composition of the peptide. The average width (mass range) of said isotopic pattern shall be denoted |Δ(m/z)ip| and the average “distance” (or mass difference) between monoisotopic peaks (caused by molecular ions of different chemical composition) as |Δ(m/z)mi|. A critical aspect of the disclosed invention is the requirement, to rigorously enforce that the degree of separation of all preceding separation dimension (stages), here X1 through X6, shall be such that on average the inequality |Δ(m/z)ip|<|Δ(m/z)mi| holds, and that in some embodiments |Δ(m/z)mi| will actually be a multiple of |Δ(m/z)ip|, i.e., |Δ(m/z)ip|<<|Δ(m/z)mi| to reduce the probability of overlap, since such overlaps would otherwise in most cases complicate or prevent detection and/or make unambiguous the subsequent sequence determination (incl. the determination of any chemical modification). One of the disclosed fundamental technical concept is that the smaller |Δ(m/z)ip| is compared to |Δ(m/z)mi|, the more likely is the successful execution of the entire process, i.e., the chance of finding a biological signature or similar insight. In other words, the degree of separation must on average always be sufficiently high to ensure that during said at least one analytical process only a negligible degree of detrimental interference between said groups of essentially similar molecules or decomposition products thereof occurs with respect to obtaining said at least one characteristic quantity. This is in fact an extraordinary demand on the degree of separation, as eluded to further down. In the illustrated example this first mass-spectroscopic sub-step is followed in many embodiments by at least one sub-step 123, which is based on one ore more physical and/or chemical methods to affect controlled fragmentation, which breaks off individual monomers, at least partially down to the monomer level (e.g. amino acids in case of proteins and nucleic acids in case of DNA and RNA). Typically various numbers of monomers are removed from the original molecular ion depending on chosen parameters of the used process. Thus again, a characteristic mix of complete and incomplete fragments is produced, from which sequence information can be obtained. (This fragmentation methods may include, but shall not be limited to collision induced dissociation, electron capture dissociation, electromagnetic radiation of sufficient quantum energy, or any other suitable method.) In at least one subsequent sub-step 124, which determines at least one characteristic quantity of said fragments, from which ultimately the chemical composition can be deduced, the sequence information is derived, including any chemical modification on any monomer. Illustrated in FIG. 1 is another mass-spectrometric sub-step, referred to as MS-MS or MS2. FIG. 2 illustrated the increasing width of the isotopic pattern with increased molecular mass. Plotted are simulated spectra (based in the known isotopic distribution of elements) of 3 hypothetical peptides with different numbers of identical amino acids: Pro10 (10 Prolines), Pro20 (20 Prolines), and Pro40 (40 Prolines), all assumed to be singly charges by protonation. Theoretical peak positions are drawn as infinitely “thin” lines (assuming infinite mass resolution. For illustration purposes only, typical curves have been graphically overlayed on some of the large peaks, to convey the appearance of a typical mass spectrum, assuming all peaks are resolved. (Realistically, the ideal infinitely thin peak would be convoluted by a function describing the mass resolution of an actual instrument, which can vary widely.) FIG. 3 shows as a practical example a strongly zoomed-in portion of a mass spectrum of a tryptic digest of human histone H4 (a protein occurring in humans, which is of critical importance for DNA coiling and gene regulation), illustrating how closely spaced peaks may occur (even if there are only peptides from 1 protein in this particular sample and the protein is relatively small). The monoisotopic peak at m=1325.75 u corresponds to the [25-36] peptide sequence DNIQGITKPAIR (no missed cleavage), and the next monoisotopic peak at m=1336.72 u corresponds to the [45-46] peptide RISGLIYEETR (one missed cleavage, but of course usable for obtaining sequence information) and here occurring at a dynamic range of only 10:1. The mass difference between both monoisotopic peaks is Δ(m/z)mi=10.97 u, which is just sufficient to enable unambiguous identification. Each monoisotopic peak is followed by several isotopic peaks, which determine the total width of the isotopic pattern per fragment (here peptide), here approximately Δ(m/z)mi. =5 u. If an unknown biopolymer (e.g. protein) mixtures are analyzed, overlapping of these peaks must predominantly be avoided because otherwise obtaining full and unambiguous sequence information (including any chemical modifications) without prior knowledge becomes effectively impossible, in particular also due to the typically much larger dynamic range. This illustrates again the need for said extremely high degree of separation (as well as very high SNR, specifically of the ion source) and the use if several different fragmentation methods in said second process step. As pointed out above, said extreme demands in terms of separations will cause in all but the most trivial cases a very large number of measurements, which necessitate the use of automated and/or robotic high-throughput systems with strongly reduced signal acquisition time, which can perform the described process steps autonomously, uninterrupted continuous operation, and predominantly without user interventions. FIG. 4 provides a rendering, which crudely depicts some of the elements, which may in some embodiments contribute to the required level of system performance. In many embodiments such systems will be centered around a high performance ion sources, since the ion source has critical impact on the entire system performance, namely sensitivity, speed (throughput), SNR, linearity, and quantitative performance. In some embodiments custom-built ion sources may be connected to commercially available mass spectrometers. Here depicted, as one example, is a high-end triple-quad TOF MS. The relatively large main ion source chamber and the attached interface chamber (for sample carrier exchange) have in the depicted illustration large gate valves to enable the transfer of relatively large sample carriers. Further, schematically rendered are a high power, highly stable, solid-state laser, typically with very high repetition rate, to support sample molecule desoption. Correspondingly strengthened laser beam delivery optics and computer controlled zoom, focus, and attenuation optics are partially illustrated. In some embodiments the laser beam itself is scanned two-dimensionally at a high rate. In other embodiments the beam (pulse) energy is sufficient a achieve at a laser spot size, which is of approximately the size of a sample spot, a flux sufficient to desorb individual sample spots without optical or mechanical scanning, solely by rapidly repeated pulse exposure. Typically, 2D sample carrier movement/alignment and robotic sample carrier introduction/exchange are fully automatic for extended periods of time involving several sample carriers. In some embodiments sample spots desorption, ionization, analysis, and sample carriers and/or laser relocation to the next sample spot may occur in substantially less than one second. In typical embodiments also high-resolution video image acquisition is used to monitor and in some embodiments to control the sample spot alignment and/or the desorption process. In such embodiments large windows, at least on one side of the ion source chamber, are used to enable optical access (video observation, laser input, input laser monitoring, reflected laser output, reflected laser beam monitoring, fluorescence monitoring, or any other secondary effect etc.). Typically the employed glass (quartz) is highly pure (low content of any contamination) and has low attenuation at a wide wavelength range, typically comprising UV and visible light, in some embodiments from UV to IR. Furthermore, stylistically illustrated are (only a single) 2D-HPLC system and robot for sample handling, incl. digestion, and sample spotting on sample carriers. In typical embodiments this part of the setup will be more complex. Also illustrated are 2 6-axis robots for handling of microtiter plates and of sample carriers, incl. carrier insertion into and removal from the ion source. While the illustrated sample carriers resemble 1536 spot plates, in typical embodiments these carriers will be larger and hold more sample spots. This enables to reduce the time penalty for sample carrier exchange (in and out of the ion source), which involves various sequential mechanical movements, as well as venting and pumping of various compartments, all of which requires time spans typically on the order of minutes, which are typically larger than the average spectrum acquisition time. Much like throughput and efficiency of the microelectronics industry has benefited from using increasingly larger wafers (with more chips), so will the disclosed bio-analytical method benefit from very large sample carriers. In some embodiments such carriers may have a surface area (on which sample spots are deposited) on the order of several hundred cm2, or even more. In some embodiments silicon wafers (optionally coated) will be used. In some embodiments such silicon wafers have functioning semiconductors on (in) them and/or metallic wiring, which is used to control and/or monitor aspects of the desorption and/or ionization, an/or analytical process. Furthermore illustrated are additional vacuum components: A high-power turbo pump for the custom-built ion source, connected to a very large rough pump, as well as another additional (smaller) rough pump to support the rough vacuum generation for the mass spectrometer itself, since the ion source may transfer more gas into the mass spectrometer, than it was designed to handle. In typical embodiments a comprehensive system for self-monitoring, self-protection (thermal, vacuum, electric, optics), as well as for protection of an operator or observer (e.g. against injury due to laser light or robots) is also employed. Numerous details incl. cables, fibers, temperature control, additional supporting structures, etc. are omitted in FIG. 4. Again, this illustration is to be interpreted only as a course conceptual depiction and many other arrangements at least in part based on some of the mentioned components will be apparent to those skilled in the art. In particular, in some embodiments a relatively large plurality of separation sub-systems (performing process steps one and/or two) may produce prepared sample carriers, which are transferred to a smaller plurality of high performance ion sources and mass spectrometers. In some embodiments a relatively small plurality of separation sub-systems (performing process steps one and/or two) may produce prepared sample carriers, which are transferred to a larger plurality of high performance ion sources and mass spectrometers. In some embodiments a plurality of the disclosed predominantly automatic and/or robotic high-throughput systems for the analysis of mixtures of biopolymers will operate in parallel on one primary sample, in order to reduce the time for obtaining the desired information. In some embodiments a plurality of such pluralities may perform such task inside a large facility and do so at least in part as a service for clients, which submit samples for analysis. DETAILED DESCRIPTION OF THE INVENTION As pointed out, the detection and identification of peptides and proteins faces one decisive problem: In contrast to DNA, there is no equivalent of PCR for proteins, i.e., proteins cannot be amplified chemically. Furthermore, proteins are more complex from a combinatorial standpoint (20 amino acids vs. 4 nucleic acids). This means that the sensitivity (and as a related parameter speed) has to come exclusively from the physical measurement. In principle, it is possible to determine the amino acid sequence of a (small) protein purely by chemical and separation means, i.e., Edman degradation (1950) and Bergmann degradation (1932). In fact, the first full sequence of a protein was determined long before the first gene was sequenced: Frederick Sanger sequenced bovine insulin in two steps in 1951 and 1952 (Sanger, Nobel lecture 1958), whereas the first genome (of bacteriophage Phi X 174) was obtained in 1977, also by Sanger (Sager et al., 1977). However, such methods to identify proteins are highly laborious and slow, requires considerable amounts of a purified protein, and have several other limitation. Thus, from a practical standpoint there are fundamentally only two ways of detecting and identifying proteins: (A) methods based on specific molecular binding events and (B) mass spectrometry (MS)-based methods. Methods utilizing affinity-based specific molecular binding include any antibody-based methods—naturally occurring or synthesized—, but also including e.g. aptamer-based (i.e., synthetic) chip-mediated protein detection methods et cetera. Typical examples for antibody-based methods are enzyme-linked immunosorbent assays (ELISA), flow cytometry and variants thereof such as ‘mass cytometry’ (CyTOF)). Such methods can in some cases be highly sensitive, enabling single cell analysis in case of flow cytometry (ELISA is less sensitive). In many other case the affinity of certain antibodies is simply not high enough, e.g. for practical tests based on blood samples. In general, antibody-based methods are relatively cheap as long as one is only looking for a few proteins (thus one reveals only a tiny fraction of all proteins present in a cell). Nevertheless, the limited success of such highly restricted antibody based biomarker searches—based on information from very few protein levels—clearly indicates that understanding proteins is the key to clinically usable biomarkers. However, comprehensive protein mixture analysis using methods based on specific molecular binding, including antibody-based methods, is (a) either physically impossible (in the case of flow cytometry due to wavelength overlap), (b) even if possible would be prohibitively expensive and/or impossible as it would require libraries of antibodies (or other molecules) against all known human proteins including posttranslational modification (PTMs, estimated on the order of several million) and (c) does not generally allow the clear identification and location (on which amino acid) of PTMs. Thus, methods based on specific molecular binding, including antibody-based methods, are better suited for quick and cheap diagnostic tests, once one (or more) protein biomarker has already been identified (and such molecular binding are specific enough). Conversely, at least in part on MS-based methods are, in principle, well suited for the discovery of biomarkers (based on the analysis of complex mixture), since they can detect any peptide and protein with any PTM. However, they are orders of magnitude less sensitive and intrinsically not quantitative (as a result of different proton affinities of amino acids). However, in order to obtain quantitative information from MS measurements investigations have resorted to complicated tagging methods (incl. isotope-coded affinity tags (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), tandem mass tags (TMT), metal-coded tags (MeCATs), and stable isotope labeling with amino acids in cell culture (SILAC) etc.). Unfortunately, this is either too expensive and time-consuming for comprehensive analysis, or brings one straight back to the problems associated with antibodies, or is not clinically applicable to humans. Hence, in principle it is clear that mass-spectrometry based methods have the potential of finding markers or similar signature information. As eluded to above, previous attempts have failed for various reason, both biological as well as metrological, specifically approaches based on so called shotgun proteomics, whereby a primary sample containing a mix of proteins is first enzymatically digested, then fractionated, and the obtained fractions are then subjected to e.g. mass-spectrometric analysis. The problem with this approach is, if dealing with complex mixtures and little prior information about their composition, that some information about the composition of the contain proteins is lost, which would necessitate to unambiguously identify all protein fragments (peptides) and again fragments thereof (amino acids), including all potential chemical modifications (PTMs) of said proteins. Said “shotgun” approaches may be suitable if a sufficiently high degree of prior information concerning the potential content of a sample, e.g. a protein mix is available, specifically if the goal of the analysis to confirm (or refute) the presence e.g. of specific proteins. Such statements can be made based on the detection of a few characteristic protein fragments (peptides), but no statements can be made about any other potentially present modifications on other fragments of such a protein. However, this is required for comprehensive biomarker searches in predominantly unknown protein mixtures. Furthermore, previous biomarker searches have typically attempted to artificially reduce the number of mass-spectrometric measurements and/or degree of separation, with the fatal result of loosing large amount of information due to detrimental interference (in a general physical and or metrological sense, not a sense of wave physics) of signals within each measurement. As a result, MS-based biomarker searches at present produce markers with insufficient sensitivity and specificity for general clinical application. What has been missing thus far is a truly comprehensive and sufficiently sensitive analysis of all proteins, preferably from very small amounts of tissue or serum, ideally even at the single cell level. Since no PCR exists for proteins, a physical solution to a biochemical problem is required. A critically limiting factor is the ion source performance and technology. A related factor is the degree of sample separation. There are at least two fundamental technical parameters, which limit the amount of information—here typically the number of different peak position (by whatever definition)—which can be extracted from a (mass-) spectrum: Signal-to-noise ratio (and thus dynamic range) as well as resolution. Every instrument, which determines molecular mass or mass-to-charge ratio, has a finite resolution, i.e. the ability to resolve different masses or mass-to-charge ratios. Thus, there is always a finite number of individual peaks which can unambiguously be identified within
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