Siri of the cell: what biology could learn from the iPhone

Anne-Ruxandra Carvunis; Trey Ideker

doi:10.1016/j.cell.2014.03.009

Siri of the cell: what biology could learn from the iPhone

Cell. 2014 Apr 24;157(3):534-8. doi: 10.1016/j.cell.2014.03.009.

Authors

Anne-Ruxandra Carvunis¹, Trey Ideker²

Affiliations

¹ Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
² Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA. Electronic address: trey@bioeng.ucsd.edu.

Abstract

Modern genomics is very efficient at mapping genes and gene networks, but how to transform these maps into predictive models of the cell remains unclear. Recent progress in computer science, embodied by intelligent agents such as Siri, inspires an approach for moving from networks to multiscale models able to predict a range of cellular phenotypes and answer biological questions.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Artificial Intelligence*
Biological Ontologies*
Cell Biology* / trends
Gene Regulatory Networks
Models, Biological*
Natural Language Processing
Systems Biology

Abstract

Publication types

MeSH terms

Grants and funding