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Eran Segal

Eran Segal (Hebrew: ערן סגל; born 15 November 1973) is a computational biologist professor 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] Segal also works as an epidemiologist.^[7]

He gained his BAinComputer Science and Economics from Tel Aviv University in 1998^[2] and his PhD from Stanford University under a Fulbright Scholarship in 2004 advised by Daphne Koller.^[8]

In 2007, he was awarded the Overton Prize by the International Society for Computational Biology.^[1] In 2011, he was made a professor at the Weizmann Institute of Science.

Over the years, Segal published more than 140 articles in scientific and medical journals, of which about 20 in the journal Nature Cell Biology.

Segal is a proponent of the idea there is no "one size fits all" diet, in the sense that people will respond differently to certain types of food. Through a study utilizing continuous glucose monitoring and food journals, he produced some evidence that the glucose response to specific foods differ significantly between people. He hypothesized that personalized food plans based on further research could be beneficial in reducing the occurrence of diabetes. Later, he employed blood DNA testing, feces analysis (gut bacteria) to gather data which was analysed with a machine learning method to create personalized diets that were expected to improve glucose responses after eating. This method was tested on a population size of 26, the results of the study supported his hypothesis, though required further testing.^[9][10]