Eran Segal: Computing expression

Credit: Photo: Ahikam Seri" /> 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

| 2 min read

Register for free to listen to this article
Listen with Speechify
0:00
2:00
Share

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.

Segal also worked on a model ...

Interested in reading more?

Become a Member of

The Scientist Logo
Receive full access to digital editions of The Scientist, as well as TS Digest, feature stories, more than 35 years of archives, and much more!
Already a member? Login Here

Keywords

Meet the Author

  • Jonathan Scheff

    This person does not yet have a bio.

Published In

Share
May digest 2025 cover
May 2025, Issue 1

Study Confirms Safety of Genetically Modified T Cells

A long-term study of nearly 800 patients demonstrated a strong safety profile for T cells engineered with viral vectors.

View this Issue
iStock

TaqMan Probe & Assays: Unveil What's Possible Together

Thermo Fisher Logo
Meet Aunty and Tackle Protein Stability Questions in Research and Development

Meet Aunty and Tackle Protein Stability Questions in Research and Development

Unchained Labs
Detecting Residual Cell Line-Derived DNA with Droplet Digital PCR

Detecting Residual Cell Line-Derived DNA with Droplet Digital PCR

Bio-Rad
How technology makes PCR instruments easier to use.

Making Real-Time PCR More Straightforward

Thermo Fisher Logo

Products

fujirebio-square-logo

Fujirebio Receives Marketing Clearance for Lumipulse® G pTau 217/ β-Amyloid 1-42 Plasma Ratio In-Vitro Diagnostic Test

The Scientist Placeholder Image

Biotium Launches New Phalloidin Conjugates with Extended F-actin Staining Stability for Greater Imaging Flexibility

Leica Microsystems Logo

Latest AI software simplifies image analysis and speeds up insights for scientists

BioSkryb Genomics Logo

BioSkryb Genomics and Tecan introduce a single-cell multiomics workflow for sequencing-ready libraries in under ten hours