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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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Proceedings ArticleDOI

An XML application for genomic data interoperation

TL;DR: This paper illustrates the usefulness of XML in representing and interoperating genomic data between two different data sources (Snyder's laboratory at Yale and SGD at Stanford) and compares the locations of transposon insertions with the chromosomal locations of the yeast open reading frames stored in SGD.
Book ChapterDOI

Semantic Web Standards: Legal and Social Issues and Implications

TL;DR: This chapter will describe the social process of creating standards within academic science, and outline some of the legal concerns -particularly related to antitrust and intellectual property issues, making some suggestions that might assist the regulation of difficulties of a legal nature in standardizing data and prevent a legal morass from arising out creating and setting standards for the Semantic Web.
Posted ContentDOI

Leveraging protein dynamics to identify cancer mutational hotspots in 3D-structures

TL;DR: This work presents a framework to identify driver genes using a dynamics-based search of mutational hotspots in cancer-associated genes using the TCGA pan-cancer atlas missense mutation catalog.
Journal ArticleDOI

Recovering genotypes and phenotypes using allele-specific genes

TL;DR: In this article, the authors report that, despite not containing explicit variant information, a list of genes known to be allele-specific in an individual is enough to recover key variants and link the individuals back to their genotypes and phenotypes.
Posted ContentDOI

Cross-platform transcriptomic profiling of the response to recombinant human erythropoietin.

TL;DR: This study provides a knowledge base of genes characterising the responses to recombinant human erythropoietin through cross-platform comparison and validation and shows that total RNA sequencing combined with DNB-seq produced a multitude of genes of biological relevance and significance in response to recombination.