Short 150-word profile

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Mark Gerstein is the Albert L Williams professor of Biomedical Informatics at Yale University. He is the co-director the Yale Computational Biology & Bioinformatics Program and has appointments in the Department of Molecular Biophysics & Biochemistry and the Department of Computer Science. He received his AB in physics summa cum laude from Harvard College and his PhD in chemistry from Cambridge. He did post-doctoral work at Stanford and took up his post at Yale in early 1997. Since then he has published appreciably in the scientific journals, with >400 publications in total, including a number of them in prominent venues, such as Science, Nature, and Scientific American. (His current publication list is at http://papers.gersteinlab.org .) His research is focused on bioinformatics, and he is particularly interested in data science & data mining, macromolecular geometry & simulation, and human genome annotation & cancer genomics.  
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Mark Gerstein is the Albert L Williams professor of Biomedical Informatics at Yale University. He is the co-director of the Yale Computational Biology & Bioinformatics Program and the Center for Biomedical Data Science. He has appointments in the Departments of Molecular Biophysics & Biochemistry, Computer Science and Statistics & Data Science. He received his AB in physics summa cum laude from Harvard College and his PhD in chemistry from Cambridge. He did post-doctoral work at Stanford and took up his post at Yale in early 1997. Since then, he has published appreciably in the scientific journals, with >550 publications in total, including a number of them in prominent venues, such as Science, Nature, and Scientific American. (His current publication list is at http://papers.gersteinlab.org .) His research is focused on biomedical data science, and he is particularly interested in data mining, macromolecular geometry & simulation, human-genome annotation, disease genomics and genomic privacy.
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(143 words, updated 30-Sep-2015)
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(151 words, updated 1-Dec-2019)
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[http://info.gersteinlab.org/index.php?title=Short_150-word_profile&oldid=3783 older 2015 version]
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After graduating from Harvard summa cum laude with an A.B. in physics in 1989, Prof. Mark Gerstein earned a doctorate in theoretical chemistry and biophysics from Cambridge University in 1993. He did postdoctoral research in bioinformatics at Stanford University from 1993 to 1996. He came to Yale in 1997 as an assistant professor in the Department of Molecular Biophysics and Biochemistry, and since 1999, in the Computer Science Department. He was named an associate professor in 2001, and the following year became co-director of the Yale Computational Biology and Bioinformatics Program. Gerstein has published appreciably in the scientific literature, with >400 publications in total, including a number of them in prominent venues, such as Science, Nature, and Scientific American. His research is focused on bioinformatics, and he is particularly interested in data science & data mining, macromolecular geometry & simulation, and human genome annotation & cancer genomics.
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(147 words, updated 7-Dec-2015)
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Latest revision as of 20:05, 1 December 2019

Mark Gerstein is the Albert L Williams professor of Biomedical Informatics at Yale University. He is the co-director of the Yale Computational Biology & Bioinformatics Program and the Center for Biomedical Data Science. He has appointments in the Departments of Molecular Biophysics & Biochemistry, Computer Science and Statistics & Data Science. He received his AB in physics summa cum laude from Harvard College and his PhD in chemistry from Cambridge. He did post-doctoral work at Stanford and took up his post at Yale in early 1997. Since then, he has published appreciably in the scientific journals, with >550 publications in total, including a number of them in prominent venues, such as Science, Nature, and Scientific American. (His current publication list is at http://papers.gersteinlab.org .) His research is focused on biomedical data science, and he is particularly interested in data mining, macromolecular geometry & simulation, human-genome annotation, disease genomics and genomic privacy.

(151 words, updated 1-Dec-2019)


older 2015 version

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