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Ryan Poplin

Showing results (1-10 of 20) with videos related to

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JAMA|July 20, 2021
Challenges of Accuracy in Germline Clinical Sequencing DataRyan Poplin, Justin M Zook, Mark DePristo
Bioinformatics (Oxford, England)|March 28, 2019
GenomeWarp: an alignment-based variant coordinate transformationCory Y McLean, Yeongwoo Hwang, Ryan Poplin, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|March 14, 2019
CrowdVariant: a crowdsourcing approach to classify copy number variantsPeyton Greenside, Justin Zook, Marc Salit, et al.
Nature Biomedical Engineering|April 25, 2019
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learningRyan Poplin, Avinash V Varadarajan, Katy Blumer, et al.
Quantitative Biology (Beijing, China)|June 4, 2021
Identifying viruses from metagenomic data using deep learningJie Ren, Kai Song, Chao Deng, et al.
BMC Genomics|March 14, 2015
The distribution and mutagenesis of short coding INDELs from 1,128 whole exomesDanny Challis, Lilian Antunes, Erik Garrison, et al.
Investigative Ophthalmology & Visual Science|July 20, 2018
Deep Learning for Predicting Refractive Error From Retinal Fundus ImagesAvinash V Varadarajan, Ryan Poplin, Katy Blumer, et al.
ACS Synthetic Biology|November 5, 2021
Evolution of Functionally Enhanced α-l-Threofuranosyl Nucleic Acid AptamersCailen M McCloskey, Qingfeng Li, Eric J Yik, et al.
Nature Biotechnology|September 25, 2018
A universal SNP and small-indel variant caller using deep neural networksRyan Poplin, Pi-Chuan Chang, David Alexander, et al.
Current Protocols in Bioinformatics|November 29, 2014
From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipelineGeraldine A Van der Auwera, Mauricio O Carneiro, Christopher Hartl, et al.
Pageof 2

Showing results (1-10 of 20) with videos related to

Sort By:
Pageof 2
JAMA|July 20, 2021
Challenges of Accuracy in Germline Clinical Sequencing DataRyan Poplin, Justin M Zook, Mark DePristo
Bioinformatics (Oxford, England)|March 28, 2019
GenomeWarp: an alignment-based variant coordinate transformationCory Y McLean, Yeongwoo Hwang, Ryan Poplin, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|March 14, 2019
CrowdVariant: a crowdsourcing approach to classify copy number variantsPeyton Greenside, Justin Zook, Marc Salit, et al.
Nature Biomedical Engineering|April 25, 2019
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learningRyan Poplin, Avinash V Varadarajan, Katy Blumer, et al.
Quantitative Biology (Beijing, China)|June 4, 2021
Identifying viruses from metagenomic data using deep learningJie Ren, Kai Song, Chao Deng, et al.
BMC Genomics|March 14, 2015
The distribution and mutagenesis of short coding INDELs from 1,128 whole exomesDanny Challis, Lilian Antunes, Erik Garrison, et al.
Investigative Ophthalmology & Visual Science|July 20, 2018
Deep Learning for Predicting Refractive Error From Retinal Fundus ImagesAvinash V Varadarajan, Ryan Poplin, Katy Blumer, et al.
ACS Synthetic Biology|November 5, 2021
Evolution of Functionally Enhanced α-l-Threofuranosyl Nucleic Acid AptamersCailen M McCloskey, Qingfeng Li, Eric J Yik, et al.
Nature Biotechnology|September 25, 2018
A universal SNP and small-indel variant caller using deep neural networksRyan Poplin, Pi-Chuan Chang, David Alexander, et al.
Current Protocols in Bioinformatics|November 29, 2014
From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipelineGeraldine A Van der Auwera, Mauricio O Carneiro, Christopher Hartl, et al.
Pageof 2