Bioinformatics in the information age
There is a well-known story about the blind man examining the elephant: the part of the elephant examined determines his perception of the whole beast. Perhaps bioinformatics--the shotgun marriage between biology and mathematics, computer science, and engineering--is like an elephant that occupies a large chair in the scientific living room. Given the demand for and shortage of researchers with the computer skills to handle large volumes of biological data, where exactly does the bioinformatics elephant sit? There are probably many biologists who feel that a major product of this bioinformatics elephant is large piles of waste material. If you have tried to plow through Web sites and software packages in search of a specific tool for analyzing and collating large amounts of research data, you may well feel the same way. But there has been progress with major initiatives to develop more computing power, educate biologists about computers, increase funding, and set standards. For our purposes, bioinformatics is not simply a biologically inclined rehash of information theory (1) nor is it a hodgepodge of computer science techniques for building, updating, and accessing biological data. Rather bioinformatics incorporates both of these capabilities into a broad interdisciplinary science that involves both conceptual and practical tools for the understanding, generation, processing, and propagation of biological information. As such, bioinformatics is the sine qua non of 21st-century biology. Analyzing gene expression using cDNA microarrays immobilized on slides or other solid supports (gene chips) is set to revolutionize biology and medicine and, in so doing, generate vast quantities of data that have to be accurately interpreted (Fig. 1). As discussed at a meeting a few months ago (Microarray Algorithms and Statistical Analysis: Methods and Standards; Tahoe City, California; 9-12 November 1999), experiments with cDNA arrays must be subjected to quality control. Variables as simple as temperature and illumination differences across a microarray slide can alter readings. Between slides, additional variables add to the difficulty of comparison. For example, John Quackenbush (The Institute for Genomic Research) described the complexities associated with assuring quality control between microarray slides in a presentation both humorous and disquieting in which he demonstrated how air conditioning can affect sample readouts. Manfred Zorn (Lawrence Berkeley National Laboratory, LBNL), chair of a working group on standards, launched a preliminary effort to lay down definitions and standards for microarray analysis with particular emphasis on experimental design, measurement, and analysis documentation.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Director, Office of Science
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 842489
- Report Number(s):
- LBNL-45777; R&D Project: 442201; TRN: US200516%%57
- Resource Relation:
- Other Information: Journal Publication Date: 2/18/2000
- Country of Publication:
- United States
- Language:
- English
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