IT Infrastructure. Overview of Presently Available Software Tools

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1 data, they show in leukemic studies that Bayesian networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data Scope of the Fields A discussion of B&CB can be so wide-ranging as to become confusing and unmanageable unless the boundaries of the inquiry are clearly delineated. In the following section, we will briefly describe the IT infrastructure and its management. IT Infrastructure B&CB requires a powerful IT infrastructure network which has grown in tandem with this field over the years. It is composed of a vast web of wires, routers, bridges, mainframes, servers, computers, and other hardware that makes possible the production, elaboration and movement of information throughout the client organization (business, academic facility, government lab). Computer software and different network operating platforms also complicate the infrastructure, including DOS, the several Windows platforms, Apple, Unix, Novell, Banyan, and many others. Then there is the information infrastructure, which includes library databases, CD- ROM resources, and remote library access. These large and complex systems require constant upgrading and monitoring. B&CB requires a powerful IT infrastructure network which has grown in tandem with this field over the years Overview of Presently Available Software Tools One of the basic ground rules of software management and development was enunciated by Parker, et. al. 9 : most experts are inexpert at most things. By this, the authors are referring to the fact that researchers are inexpert when it comes to manipulating web pages and using tools and, in fact, may not even know that a given tool for solving a particular problem exists. Since this leads workers to the time-consuming task of composing tool chains by hand, the authors argue for an in-the-large perspective for large bioinformatics projects. They give examples of application of the make utility which was developed for automatically managing large applications. Make is a UNIX utility intended to automate and optimize the construction of programs. It is particularly relevant to bioinformatics as it can develop programs consisting of many components or source files. It is notable for its ability to reduce the possibility of human error in backing entries from the command line. Reproduction prohibited 13

2 Table 3.3. Programs in Systems Biology (cont.) Programs in Systems Biology Institution Program Technologies Lewis-Sigler Institute for Integrative Genomics Life Sciences Institute // Merrimack Pharmaceuticals Cambridge, MA // Okinawa Institute of Science and Technology Onna Village, Okinawa, Japan Princeton University (Princeton, NJ). Interdisciplinary research groups University of Michigan (Ann Arbor, MI). 30 research teams collaborate on projects Biotech firm New graduate university Basic research on the systems that control cell growth, neural circuits, synthesis of carbohydrates, and proteinprotein interactions Networks that genes and proteins in a cell use to sense and adapt to stimuli Network biology to find new drugs for cancer and autoimmune diseases Emphasizes integrative research in biosystems Source: Insight Pharma Reports There is an extensive literature of systems biology investigation (28,000 citations in MEDLINE); much of it funded by private companies. Three important contributors are Genstruct, which is developing complex models of diseases combining analysis of genes, proteins, and metabolic parameters. Other examples include Entelos, evaluating mathematical modeling to study diseases, and Merrimack Pharmaceutical, which is testing information on signaling networks in tumor cells to determine which drugs are effective. A fourth example is Avalon Pharmaceuticals, noted for its gene expression technology for determination of likely responders to therapies. 48 SystemsX is an international project that draws on expertise and financial support from Hoffman La Roche and Novartis, with their headquarters in Basel. The universities involved in the work are both Swiss and international institutions, representing top academic groups. The goal, by pooling talent and resources, is to generate and manage in an unparalleled fashion the vast deluge of data that will flow into the project. Reproduction prohibited 51

3 Chapter 4 The Dilemma ahead for bioinformatics 4.1. Data Proliferation: The Good News and Challenges The unprecedented amount of data flowing out of computer systems affects every aspect of our society. While the problems of data overload originally referred to challenges associated with the storage of hardcopy on paper, the question now turns on the issue of electronic storage. Chris Anderson of Wired Magazine puts forth an interesting proposition that looks at the bright side of the data proliferation issue. He begins his argument with what appears to be a dubious proposition: All models are wrong, but some are useful. According to Anderson, in an era of massively abundant data, We don t have to settle for wrong models. Indeed, we don t have to settle for models at all. As near as Anderson s argument can be followed, he seems to be saying that Google conquered the advertising world without knowing anything about the products, just collecting huge amounts of data and following them to their conclusion, which in this case was a superior search engine and advertising vehicle. Anderson quotes Peter Norvig, Google s research director, who strongly endorses George Box s maxim: All models are wrong, and increasingly, you can succeed without them. For instance, Anderson offers the case of Newton s Laws of Motion, which were eventually replaced by Einstein s more accurate description of the Laws of Relativity, claiming that Newtonian Mechanics is a wrong model, which was replaced by the more appropriate (but not completely satisfactory) Einsteinian views of the universe. However, he appears to have missed the point. Newton s model wasn t wrong; Reproduction prohibited 75

4 5.5. Kevin Davies, Editor in Chief, BioIT World IPR: What are the major challenges that the field of B&CB faces in the coming years? Are the glut of data, storage and retrieval of -omics data from many sources a concern? KD: The data glut, particularly surrounding areas of next-generation sequencing and image analysis, is a huge concern, absolutely! One of the latest entrants in the next-generation sequencing field, Complete Genomics, is planning to build a genome center in California with 200 instruments sequencing 20,000 human genomes and a 50-petabyte data center by Single sequencing runs lasting a few days generate terabytes of data, so much that the primary image data has to be considered a transient disposable by-product of the experiment. Handling the storage, retrieval, and integration of these data is also challenging, and I don t think there are any standard solutions. Having said that, I would note that Isilon s storage is emerging as a popular choice among leading genome centers (Broad Institute, Wellcome Trust Sanger Institute) and industry (Complete Genomics), for its scalability and ease of use. IPR: Much sequencing information involves privacy issues. Is it possible to protect individual confidentiality while at the same time enduring maximum access to the data? KD: The much delayed passage of GINA (the Genetic Information and Non-Discrimination Act) in 2008 has provided much reassurance that individual genetic data can be kept private and not used as the basis to deny individuals employment or health insurance. There is still room for improvement, however. I have heard some scientists express concern about Google s links to the personal genomics service, 23andMe, on the privacy front, giving that as a reason why they don t want to submit their samples to the company. On the other hand, George Church s Personal Genome Project, which has released genetic and medical data on its first ten volunteers, aims to debunk much of the stigma about genetic information and privacy. After all, we all have our share of genetic quirks and predispositions. Reproduction prohibited 101

5 Conclusions time a cancer consists of billions of cells spread through every sensitive organ and structure, the prospect of a successful outcome becomes vanishingly small. As mentioned earlier in this report, cancer cells tend to have extremely high mutation rates and undergo rapid and profound genetic and epigenetic changes, which will make them resistant to virtually any therapeutic option that the pharmacologist can devise. 86,87 The second cause of this lack of significant progress is the focus on treatment to the exclusion of diagnosis. Sensitive, cheap, and noninvasive tests for blood borne proteins as cancer markers is a powerful tool in the war cancer but has been all but ignored over the years (Table 6.1). PubMed lists only 5,294 titles under the heading, cancer biomarkers, yet there are 266,899 listings for cancer therapy. It is well known that extremely lethal cancers are highly treatable at early stages. For instance, pancreatic cancer has a 5-year survival of 95% when detected early and only 5% when detected late. In addition, it is always detected late. Some of the challenges to cancer diagnostic development are spelled out in Table 6.2. Table 6.1. Biomarker Technologies Company Biomarker Program Technology Comments Abbott Laboratories Biomarker research Biomarker research DNA diagnostic for HER2 gene in breast cancer Aperio Technologies, Inc. Tissue Biomarkers Digitalizing slide-based data Tissue-based biomarkers still provide best indication of the local tumor environment Applied Biosystems Targeted Quantitation of Biomarkers in Plasma Peptide MRM-based assays and chemistry Supplies technology solutions for biomarker discovery BioSystems International Discovery and utilization of new, disease-specific protein biomarkers Monoclonal antibodybased plasma screening Designed to cut transition time from biomarker discovery to clinical diagnostics Caprion Proteomics Biomarker and target discovery collaborations CellCarta Targets for therapeutics develop ment and identification of protein biomarkers multistep process that includes mass spec detection and quantitative peptide expression profiling. Expression Pathology Inc. Protein biomarkers in archival formalin-fixed tissue Mass spectrometrybased Biomarkers of lung cancer metastasis and survival Genstruct, Inc. Identifying mechanistic biomarkers Modeling powered by molecular profiling Collaborations with Pfizer Continued Reproduction prohibited