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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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Analysis of variable retroduplications in human populations suggests coupling of retrotransposition to cell division

TL;DR: It is shown that cell division is coupled to retrotransposition and, perhaps, is even a requirement for it, and that a correct phylogenetic tree of human subpopulations based solely on retroduplications can be reconstructed.
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Personal phenotypes to go with personal genomes.

TL;DR: The power of 500 million sequences correlated with 500 million phenotypes can show both small contributions as well as help identify potential causative mutations.
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The tYNA platform for comparative interactomics

TL;DR: TYNA is a Web system for managing, comparing and mining multiple networks, both directed and undirected, that efficiently implements methods that have proven useful in network analysis, including identifying defective cliques, finding small network motifs and calculating global statistics.
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A computational approach for identifying pseudogenes in the ENCODE regions

TL;DR: This work identifies about 160 pseudogenes, 10% of which have clear 'intron-exon' structure and are thus likely generated from recent duplications, and demonstrates that the computation pipeline provides a good balance between identifying all pseudogene and delineating the precise structure of duplicated genes.
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Assessing the need for sequence-based normalization in tiling microarray experiments

TL;DR: This work investigated the importance of probe sequence composition on the efficacy of tiling microarrays for identifying novel transcription and transcription factor binding sites and developed three metrics for assessing this sequence dependence and use them in evaluating existing sequence-based normalizations from the tilingmicroarray literature.