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Anshul Kundaje

Researcher at Stanford University

Publications -  252
Citations -  43164

Anshul Kundaje is an academic researcher from Stanford University. The author has contributed to research in topics: Chromatin & Gene. The author has an hindex of 60, co-authored 203 publications receiving 32299 citations. Previous affiliations of Anshul Kundaje include Microsoft & Columbia University.

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Integrative analysis of 111 reference human epigenomes

Anshul Kundaje, +123 more
- 19 Feb 2015 - 
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.

Integrative analysis of 111 reference human epigenomes

Anshul Kundaje, +24 more
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.

An integrated encyclopedia of DNA elements in the human genome

Ian Dunham, +442 more
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
Journal ArticleDOI

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia

Stephen G. Landt, +46 more
- 01 Sep 2012 - 
TL;DR: This work discusses how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data and develops a set of working standards and guidelines for ChIP experiments that are updated routinely.
Proceedings Article

Learning important features through propagating activation differences

Avanti Shrikumar, +2 more
TL;DR: DeepLIFT (Deep Learning Important FeaTures), a method for decomposing the output prediction of a neural network on a specific input by backpropagating the contributions of all neurons in the network to every feature of the input, is presented.