PerspectivesAre you interested in submitting a Perspective Article? Be sure to read The Science Advisory Board's Editorial Guides for Perspective Articles. Click here. Advancing Scientific Understanding of Living Systems Through Computation by Stefan Unger, Ph.D. (Principal Author) Biology underlies all the life sciences. Today, without computational approaches, our potential to learn and understand the complex relationships between and among the subsets (biological response, biodiversity, genetics, medicine, etc.) would be totally thwarted. Computational Biology (CB) represents the marriage of information technology (IT) and biology, and spans many disciplines, such as bioinformatics, molecular modeling, biosimulation, clinical informatics, medical imaging, and many others. CB finds application in many areas of life science, for example, the development of human therapeutics (therapies), diagnostics (tests for the presence of particular diseases), prognostics (tests for the tendency toward, or susceptibility to, future diseases), and even forensics (identification of individuals). These fields have come to rely heavily on information processing at every stage. The goal of modern human genomics is preventive, predictive and individualized medicine. Numerous genome sequencing efforts have begun or have been completed for a wide range of crop plants and livestock, including arabidopsis (a common lab plant), bean, cotton, maize, rice, soybean, wheat, barley, oats, rye, sugarcane, pig, chicken, cow, goat, horse, rabbit and sheep. Genetically modified plants and animals can use used directly, or can be used as "factories" to produce other materials of interest, such as pharmaceuticals. Industrial applications include the development of enzymes used for industrial biocatalysis, or enzymes used directly as, for example, detergents for environmental remediation. The range of laboratories involved in CB is enormous, from single, isolated laboratories in community colleges, even advanced high schools, up through research hospitals and on to enormous multinational biopharmaceutical and agricultural biotechnology (agbio) companies such as GlaxoSmithKline, Pfizer, Lilly, Roche, AstraZeneca, Monsanto, and Bayer. In some ways, CB -- especially bioinformatics -- is called upon to clean up the mess created by the recent collision of three major paradigms:
The result is high density experimentation resulting in the generation of so much data that humans are no longer able to comprehend the information hidden within, convert it into knowledge and take appropriate action without the aid of computers. Furthermore, the globalization of research, either by multinational pharmaceutical companies, or academic collaborative networks, would be impossible without computers. Both data and compute services must be available anytime and anywhere to global research networks, or industries. Please refer to http://www.sun.com/products-n-solutions/edu/docs/briefing_in_comp_bio.pdf for a detailed discussion of computational biology, challenges and opportunities, and SunTM Global Education & Research Vision for Computational Biology. ### Excerpted with permission from "Briefing in Computational Biology," SunTM Global Education and Research, Science & Engineering, 2001. Additional contributors include Loralyn Mears, Ph.D., Simon See, Ph.D., Susan Stephens, Ph.D., John Feo and Ilya Sharapov. ### << Previous Next >> [ View All Perspectives ] |
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