Etai Jacob

Etai Jacob, PhD

Research Interest

I obtained my Ph.D. in computational biology in 2016 from Bar-Ilan University and the Weizmann Institute of Science (as a collaboration) in Israel. During my Ph.D. studies, I also worked at Compugen Ltd., developing algorithms using machine learning and statistical modelling and building data mining infrastructure for early stage drug targets discovery.

My general research interests concern data analysis and algorithm development in biology. During the last ten years, I have been working on different problems in biology (as protein structure prediction, protein folding and understanding proteins and gene expression) and the interface between computational biology and computer science (data structure and organization, databases design and data mining).

Currently, my main research focus is on the development of algorithms for the analysis of single cell RNA and DNA sequencing data to understand the transcriptional consequences and mechanisms of chromosomal abnormalities such as aneuploidy and genomic rearrangements.

Personal website


2016PhD, Bar-Ilan University and Weizmann Institute of Science (collaboration), Israel

Selected publications

  • Etai Jacob, Ron Unger and Amnon Horovitz. Codon-level information improves predictions of inter-residue contacts in proteins by correlated mutation analysis. eLife 2015;4:e08932 (2015) Highlighted in Nature Methods, 12, 1009 (2015)
  • Etai Jacob, Ron Unger and Amnon Horovitz. N-Terminal domains in two-Domain proteins are biased to be shorter and predicted to fold faster than their C-terminal counterparts. Cell Reports 3, 1051-1056 (2013)
  • Etai Jacob and Ron Unger. A Tale of Two Tails: Why are terminal residues of proteins exposed? Bioinformatics, 23(2): 225-230 (2007)
  • Etai Jacob, Amnon Horovitz and Ron Unger. Different mechanistic requirements for prokaryotic and eukaryotic chaperonins: a lattice study. Bioinformatics, 23(13):i240-i248 (2007)

More Publications

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