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By Author: moni catsfbd
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Quantitative analysis, modeling, and prediction play increasingly significant day-to-day roles in today's biomedical research. To prepare for this sea change in activities, biology majors headed for research careers need to be educated in a more quantitative manner, and such quantitative education may require the development of new types of courses. The committee recommends that all biology majors master the concepts listed below. In addition, the committee recommends that lift science majors become sufficiently familiar with the elements of programming to carry out simulations of physiological, ecological, and evolutionary processes. They should be adept at using computers to acquire and process data, carry out statistical characterization of the data and perform statistical tests, and graphically display data in a variety of representations.

Furthermore, students should also become skilled at using the Internet to carry out literature searches, locate published articles, and access major databases.

The elucidation of the sequence of the human genome has opened new vistas and has highlighted the increasing importance ...
... of mathematics and computer science in biology. The intense interest in genetic, metabolic, and neural networks reflects the need of biologists to view and understand the coordinated activities of large numbers of components of the complex systems underlying life. Biology students should be prepared to carry out in silico (computer) experiments to complement in vitro and in vivo experiments. It is essential that biology undergraduates become quantitatively literate. The concepts of rate of change, modeling, equilibria and stability, structure of a system, interactions among components, data and measurement, visualizing, and algorithms are among those most important to the curriculum. Every student should acquire the ability to analyze issues arising in these contexts in some depth, using analytical methods (e.g., pencil and paper), appropriate computational tools, or both. The course of study would include aspects of probability, statistics, discrete models, linear algebra, calculus and differential equations, modeling, and programming.

Many of the concepts above deal with types of analysis and modeling that require knowledge of computer programming. However, there is another aspect of computing that is important for the future research biologist the use of computers as tools. Computer use is a fact of life for all modern life scientists. Exposure during the early years of their undergraduate careers will help life science students use current computer methods and learn how to exploit emerging computer technologies as they arise. As computer power continues to grow rapidly, applications that were available only on supercomputers a few years ago can now be used on relatively inexpensive personal computers. Computers are essential today for obtaining information from databases, establishing relationships (e.g., using the BLAST algorithm to quantitate the similarity of a given DNA or protein sequence to all known sequences), deducing patterns (e.g., clustering genes that are regulated in concert), carrying out statistical tests, preparing plots and other graphics for presentation, and writing manuscripts for publication. Furthermore, computers are playing a central role in the laboratory in controlling equipment, obtaining data from measuring devices, and carrying out real-time analysis (e.g., image acquisition in confocal fluorescence microscopy). Research biologists are increasingly acquiring and analyzing vast amounts of data (e.g., the degree of expression of tens of thousands of genes in multiple cellular states). They will need to be conversant with new theoretical and modeling approaches to come to grips with the interplay of many simultaneously interacting components of complex systems.

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