M
Mark Gerstein
Researcher at Yale University
Publications - 802
Citations - 172183
Mark Gerstein is an academic researcher from Yale University. The author has contributed to research in topics: Genome & Gene. The author has an hindex of 168, co-authored 751 publications receiving 149578 citations. Previous affiliations of Mark Gerstein include Rutgers University & Structural Genomics Consortium.
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Average core structures and variability measures for protein families: application to the immunoglobulins.
TL;DR: A method for using a multiple alignment to identify an average structural "core", a subset of atoms with low structural variation, which allows for straightforward comparisons between variation in structure and sequence at each position in a family.
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Perspectives on ENCODE.
Michael Snyder,Thomas R. Gingeras,Jill Moore,Zhiping Weng,Zhiping Weng,Zhiping Weng,Mark Gerstein,Bing Ren,Bing Ren,Ross C. Hardison,John A. Stamatoyannopoulos,Brenton R. Graveley,Elise A. Feingold,Michael J. Pazin,Michael Pagan,Daniel A. Gilchrist,Benjamin C. Hitz,J. Michael Cherry,Bradley E. Bernstein,Eric M. Mendenhall,Daniel R. Zerbino,Adam Frankish,Paul Flicek,Richard M. Myers +23 more
TL;DR: In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.
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Of mice and men: phylogenetic footprinting aids the discovery of regulatory elements
Zhaolei Zhang,Mark Gerstein +1 more
TL;DR: A new study shows how much it improves the prediction of gene-regulatory elements in the human genome.
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RSEQtools: a modular framework to analyze RNA-Seq data using compact, anonymized data summaries
Lukas Habegger,Andrea Sboner,Tara A. Gianoulis,Joel Rozowsky,Ashish Agarwal,Michael Snyder,Mark Gerstein +6 more
TL;DR: The Mapped Read Format (MRF) is developed, a compact data summary format for both short and long read alignments that enables the anonymization of confidential sequence information, while allowing one to still carry out many functional genomics studies.
Journal ArticleDOI
Measuring the evolutionary rewiring of biological networks.
C. Shou,Nitin Bhardwaj,Hugo Y. K. Lam,Koon-Kiu Yan,Philip M. Kim,Michael Snyder,Mark Gerstein +6 more
TL;DR: A formalism based on analogy to simple models of sequence evolution was developed and used to conduct a systematic study of network rewiring on all the currently available biological networks, and it was found that, similar to sequences, biological networks show a decreased rate of change at large time divergences.