<figcaption> Credit: Photo: Ahikam Seri</figcaption>
Credit: Photo: Ahikam Seri

Eran Segal followed a meandering route to the field of computational biology. He began by earning a bachelor's degree in computer science from Tel-Aviv University in 1998, and went on to study in Stanford University's computer science department under Daphne Koller. He also studied genetics at Stanford, where he began to explore how probabilistic models can answer biologic questions.

As a graduate student Segal focused on designing computational models of gene expression. One included a method for identifying groups of coregulated genes and their regulators.1 He tested this method on yeast gene data and then applied it to transcription factor Ypl230w, protein kinase Kin82, and the phosphatase Ppt1, to predict regulation functions, targets, and conditions, which he experimentally verified. Koller says that this research joined a relatively new movement to produce testable hypotheses about regulatory relationships that could be worked out in the lab.


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