Eran Segal

From Wikipedia, the free encyclopedia
Jump to: navigation, search
Eran Segal
Nationality Israeli
Alma mater Stanford University
Tel Aviv University
Awards Overton Prize[1]
Scientific career
Institutions Weizmann Institute of Science
Doctoral advisor Daphne Koller[2]

Eran Segal is a computational biologist at the Weizmann Institute of Science.[2] He works on developing quantitative models for all levels of gene regulation,[3] including transcription, chromatin, and translation.[4][5][6]

He gained his BA in Computer Science and Economics from Tel Aviv University in 1998[2] and his PhD from Stanford University in 2004 advised by Daphne Koller.[7] In 2007 he was awarded the Overton Prize[1] by the International Society for Computational Biology. In 2011 he was made a professor at the Weizmann Institute of Science.

Personalized Nutrition[edit]

Segal has shown that there is no "One size fits all" diet, and that the very same foods can be good for some and bad for others.

Using continuous glucose monitoring and food journals, he has shown that the glucose spike after the same foods differs significantly between people. This means that personalized food plans can help fight diabetes, possibly with much less effort than usual diets.

Later, he used blood DNA testing, feces analysis (gut bacteria) along with neural networks learning to be able to predict what diet will be optimal for each person in terms of post-pranial glucose reaction.

This method was tested and shown to work on out of sample 100 new persons.[8][9]

References[edit]

  1. ^ a b Maisel, M. (2007). "ISCB Honors Temple F. Smith and Eran Segal". PLoS Computational Biology. 3 (6): e128. Bibcode:2007PLSCB...3..128M. doi:10.1371/journal.pcbi.0030128. PMC 1904388Freely accessible. PMID 17604447. 
  2. ^ a b c http://www.wisdom.weizmann.ac.il/~eran/biography.html Eran Segal biography
  3. ^ Kaplan, N.; Moore, I. K.; Fondufe-Mittendorf, Y.; Gossett, A. J.; Tillo, D.; Field, Y.; Leproust, E. M.; Hughes, T. R.; Lieb, J. D.; Widom, J.; Segal, E. (2008). "The DNA-encoded nucleosome organization of a eukaryotic genome". Nature. 458 (7236): 362–366. Bibcode:2009Natur.458..362K. doi:10.1038/nature07667. PMC 2658732Freely accessible. PMID 19092803. 
  4. ^ Segal, E.; Fondufe-Mittendorf, Y.; Chen, L.; Thåström, A.; Field, Y.; Moore, I. K.; Wang, J. P. Z.; Widom, J. (2006). "A genomic code for nucleosome positioning". Nature. 442 (7104): 772–778. Bibcode:2006Natur.442..772S. doi:10.1038/nature04979. PMC 2623244Freely accessible. PMID 16862119. 
  5. ^ Segal, E.; Shapira, M.; Regev, A.; Pe'er, D.; Botstein, D.; Koller, D.; Friedman, N. (2003). "Module networks: Identifying regulatory modules and their condition-specific regulators from gene expression data". Nature Genetics. 34 (2): 166–176. doi:10.1038/ng1165. PMID 12740579. 
  6. ^ Segal, E.; Widom, J. (2009). "From DNA sequence to transcriptional behaviour: A quantitative approach". Nature Reviews Genetics. 10 (7): 443–456. doi:10.1038/nrg2591. PMC 2719885Freely accessible. PMID 19506578. 
  7. ^ Segal, E.; Taskar, B.; Gasch, A.; Friedman, N.; Koller, D. (2001). "Rich probabilistic models for gene expression". Bioinformatics. 17 Suppl 1: S243–S252. doi:10.1093/bioinformatics/17.suppl_1.S243. PMID 11473015. 
  8. ^ "Personalized Nutrition by Prediction of Glycemic Responses". Cell. doi:10.1016/j.cell.2015.11.001. 
  9. ^ Eran Segal (2016). What is the best diet for humans.