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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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Opportunities And Obstacles For Deep Learning In Biology And Medicine
Travers Ching,Daniel Himmelstein,Brett K. Beaulieu-Jones,Alexandr A. Kalinin,Brian T. Do,Gregory P. Way,Enrico Ferrero,Paul-Michael Agapow,Wei Xie,Gail L. Rosen,Benjamin J. Lengerich,Johnny Israeli,Jack Lanchantin,Stephen Woloszynek,Anne E. Carpenter,Avanti Shrikumar,Jinbo Xu,Evan M. Cofer,David J. Harris,Dave DeCaprio,Yanjun Qi,Anshul Kundaje,Yifan Peng,Laura K. Wiley,Marwin H. S. Segler,Anthony Gitter,Casey S. Greene +26 more
TL;DR: This work examines applications of deep learning to a variety of biomedical problems -- patient classification, fundamental biological processes, and treatment of patients -- to predict whether deep learning will transform these tasks or if the biomedical sphere poses unique challenges.
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Long-range single-molecule mapping of chromatin accessibility in eukaryotes.
Zohar Shipony,Georgi K. Marinov,Matthew P. Swaffer,Nicholas A. Sinnott-Armstrong,Jan M. Skotheim,Anshul Kundaje,William J. Greenleaf +6 more
TL;DR: This strategy is based on combining the preferential methylation of open chromatin regions by DNA methyltransferases with low sequence specificity, in this case EcoGII, an N 6 -methyladenosine (m 6 A) methyltransferase, and the ability of nanopore sequencing to directly read DNA modifications.
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Spectrogram analysis of genomes
TL;DR: In this paper, the frequency-domain analysis in the genomes of various organisms using tricolor spectrograms was performed, identifying several types of distinct visual patterns characterizing specific DNA regions.
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Statistical analysis of MPSS measurements: Application to the study of LPS-activated macrophage gene expression
Gustavo Stolovitzky,Anshul Kundaje,G. A. Held,K. H. Duggar,Christian D. Haudenschild,Daixing Zhou,Thomas J. Vasicek,Kelly D. Smith,Alan Aderem,Jared C. Roach +9 more
TL;DR: The sources of noise in MPSS are analyzed and a quantitative model describing the variability between replicate MPSs assays is presented, which is extended to the determination of the significance of changes in expression levels measured over the course of a time series of measurements.
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Discovering epistatic feature interactions from neural network models of regulatory DNA sequences.
TL;DR: This work presents a new method called Deep Feature Interaction Maps (DFIM) to efficiently estimate interactions between all pairs of features in any input DNA sequence and makes significant strides in improving the interpretability of deep learning models for genomics.