Sarah S. Richardson is John L. Loeb Associate Professor of the Social Sciences at Harvard University, jointly appointed in the Department of the History of Science and the Committee on Degrees in Studies of Women, Gender, and Sexuality. She is the author of
Hallam Stevens is Assistant Professor of History in the School of Humanities and Social Sciences at Nanyang Technological University (Singapore). He is the author of
Sarah S. Richardson is John L. Loeb Associate Professor of the Social Sciences at Harvard University, jointly appointed in the Department of the History of Science and the Committee on Degrees in Studies of Women, Gender, and Sexuality. She is the author of
Hallam Stevens is Assistant Professor of History in the School of Humanities and Social Sciences at Nanyang Technological University (Singapore). He is the author of
Machine Learning and Genomic Dimensionality: From Features to Landscapes
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Published:April 2015
Adrian Mackenzie, 2015. "Machine Learning and Genomic Dimensionality: From Features to Landscapes", Postgenomics: Perspectives on Biology after the Genome, Sarah S. Richardson, Hallam Stevens
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Sequence data, the “backbone” of genomics, is in transformation, and this transformation may well change what genomes are. The changes described in this essay concern how biological processes associated with genomes are modeled. As predictive models based on machine learning techniques are brought to bear on genomic data, they increasingly target aspects of genomes—such as their variation and their manifold spatial and temporal relationality in biological processes and function—that seem most distant and difficult to derive from the relatively stable, monolithic and hence tractable forms of order found in DNA sequences. This essay poses the growing importance of predictive models for genomes as a touchstone for wider transformations in many sectors of science, industry, commerce, media and government.
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