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S Pollard

Showing results (21-30 of 642) with videos related to

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Genome Research|January 9, 2019
Most chromatin interactions are not in linkage disequilibriumSean Whalen, Katherine S Pollard
Biorxiv : the Preprint Server for Biology|November 14, 2023
Exploring the Roles of RNAs in Chromatin Architecture Using Deep LearningShuzhen Kuang, Katherine S Pollard
Nature Genetics|July 24, 2019
Reply to 'Inflated performance measures in enhancer-promoter interaction-prediction methods'Sean Whalen, Katherine S Pollard
The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences|November 25, 1998
Social support among unmarried childless elderly personsZ Wu, M S Pollard
Nature Communications|July 29, 2024
Exploring the roles of RNAs in chromatin architecture using deep learningShuzhen Kuang, Katherine S Pollard
Biorxiv : the Preprint Server for Biology|November 14, 2023
SuPreMo: a computational tool for streamlining <i>in silico</i> perturbation using sequence-based predictive modelsKetrin Gjoni, Katherine S Pollard
Proceedings of the National Academy of Sciences of the United States of America|January 20, 2019
Chromatin features constrain structural variation across evolutionary timescalesGeoff Fudenberg, Katherine S Pollard
IEEE Computer Graphics and Applications|May 9, 2014
Direct control of simulated nonhuman charactersJunggon Kim, N S Pollard
Genome Biology|April 9, 2015
Average genome size estimation improves comparative metagenomics and sheds light on the functional ecology of the human microbiomeStephen Nayfach, Katherine S Pollard
Nature Genetics|March 30, 2021
Ultraconservation of enhancers is not ultranecessaryMaureen Pittman, Katherine S Pollard
Pageof 65

Showing results (21-30 of 642) with videos related to

Sort By:
Pageof 65
Genome Research|January 9, 2019
Most chromatin interactions are not in linkage disequilibriumSean Whalen, Katherine S Pollard
Biorxiv : the Preprint Server for Biology|November 14, 2023
Exploring the Roles of RNAs in Chromatin Architecture Using Deep LearningShuzhen Kuang, Katherine S Pollard
Nature Genetics|July 24, 2019
Reply to 'Inflated performance measures in enhancer-promoter interaction-prediction methods'Sean Whalen, Katherine S Pollard
The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences|November 25, 1998
Social support among unmarried childless elderly personsZ Wu, M S Pollard
Nature Communications|July 29, 2024
Exploring the roles of RNAs in chromatin architecture using deep learningShuzhen Kuang, Katherine S Pollard
Biorxiv : the Preprint Server for Biology|November 14, 2023
SuPreMo: a computational tool for streamlining <i>in silico</i> perturbation using sequence-based predictive modelsKetrin Gjoni, Katherine S Pollard
Proceedings of the National Academy of Sciences of the United States of America|January 20, 2019
Chromatin features constrain structural variation across evolutionary timescalesGeoff Fudenberg, Katherine S Pollard
IEEE Computer Graphics and Applications|May 9, 2014
Direct control of simulated nonhuman charactersJunggon Kim, N S Pollard
Genome Biology|April 9, 2015
Average genome size estimation improves comparative metagenomics and sheds light on the functional ecology of the human microbiomeStephen Nayfach, Katherine S Pollard
Nature Genetics|March 30, 2021
Ultraconservation of enhancers is not ultranecessaryMaureen Pittman, Katherine S Pollard
Pageof 65