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4 COMPUTATIONAL TOOLS
As a factual science, biological research involves the collection and analysis of data from potentially
billions of members of millions of species, not to mention many trillions of base pairs across different
species. As data storage and analysis devices, computers are admirably suited to the task of supporting
this enterprise. Also, as algorithms for analyzing biological data have become more sophisticated and
the capabilities of electronic computers have advanced, new kinds of inquiries and analyses have
become possible.
4.1 The Role of Computational Tools,
Today, biology (and related fields such as medicine and pharmaceutics) are increasingly data-
intensive—a trend that arguably began in the early 1960s.^1 To manage these large amounts of data, and
to derive insight into biological phenomena, biological scientists have turned to a variety of computa-
tional tools.
As a rule, tools can be characterized as devices that help scientists do what they know they must do.
That is, the problems that tools help solve are problems that are known by, and familiar to, the scientists
involved. Further, such problems are concrete and well formulated. As a rule, it is critical that compu-
tational tools for biology be developed in collaboration with biologists who have deep insights into the
problem being addressed.
The discussion below focuses on three generic types of computational tools: (1) databases and data
management tools to integrate large amounts of heterogeneous biological data, (2) presentation tools
that help users comprehend large datasets, and (3) algorithms to extract meaning and useful informa-
tion from large amounts of data (i.e., to find meaningful a signal in data that may look like noise at first
glance). (Box 4.1 presents a complementary view of advances in computer sciences needed for next-
generation tools for computational biology.)
(^1) The discussion in Section 4.1 is derived in part from T. Lenoir, “Shaping Biomedicine as an Information Science,” Proceedings
of the 1998 Conference on the History and Heritage of Science Information Systems, M.E. Bowden, T.B. Hahn, and R.V. Williams, eds.,
ASIS Monograph Series, Information Today, Inc., Medford, NJ, 1999, pp. 27-45.