Computational biology in the 21st century
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Author(s)
Berger Leighton, Bonnie
Daniels, Noah
Yu, Yun William
Date Issued
August 2016
Journal
Communications of the ACM
Publisher
Association for Computing Machinery (ACM)
Citation
Berger, Bonnie, Noah M. Daniels, and Y. William Yu. “Computational Biology in the 21st Century.” Communications of the ACM 59, no. 8 (July 22, 2016): 72–80, New York, NY, USA, Association for Computing Machinery (ACM), August 2016.
Version
Author's final manuscript
Abstract
Computational biologists answer biological and biomedical questions by using computation in support of—or in place of—laboratory procedures, hoping to obtain more accurate answers at a greatly reduced cost. The past two decades have seen unprecedented technological progress with regard to generating biological data; next-generation sequencing, mass spectrometry, microarrays, cryo-electron microscopy, and other highthroughput approaches have led to an explosion of data. However, this explosion is a mixed blessing. On the one hand, the scale and scope of data should allow new insights into genetic and infectious diseases, cancer, basic biology, and even human migration patterns. On the other hand, researchers are generating datasets so massive that it has become difficult to analyze them to discover patterns that give clues to the underlying biological processes.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mathematics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1145/2957324
