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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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Copy Number Variants and Segmental Duplications Show Different Formation Signatures

TL;DR: The co- localization of SDs is analyzed and it is found that SDs are significantly co-localized with each other, resulting in a power-law distribution, which suggests a preferential attachment mechanism, i.e. existingSDs are likely to be involved in creating new ones nearby.
Journal ArticleDOI

Building integrative functional maps of gene regulation.

TL;DR: Recent and ongoing efforts to build gene regulatory maps, which aim to characterize all sequences in a genome for their roles in regulating gene expression, are discussed.
Proceedings ArticleDOI

Abstract 1279: Passenger mutation landscape in cancer genomes

TL;DR: It is shown that disruption of genetic regulatory elements in the noncoding genome correlates with altered gene expression, and overall functional burdening of various genomic elements correlate with patient survival time, and tumor clonality.
Book ChapterDOI

Fast Optimal Genome Tiling with Applications to Microarray Design and Homology Search

TL;DR: The solution to a basic online interval maximum problem via a sliding-window approach is discussed and how to use this solution in a nontrivial manner for many of the tiling problems introduced.
Journal ArticleDOI

Intensification: A Resource for Amplifying Population-Genetic Signals with Protein Repeats

TL;DR: The Intensification approach is developed, which uses the modular structure of repeat protein domains to amplify signals of selection from population genetics and traditional interspecies conservation, and is able to aggregate variants at the codon level to identify important positions in repeat domains that show strong conservation signals.