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Lior Pachter

Showing results (81-90 of 200) with videos related to

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Nature Methods|January 22, 2019
A discriminative learning approach to differential expression analysis for single-cell RNA-seqVasilis Ntranos, Lynn Yi, Páll Melsted, et al.
Bioinformatics (Oxford, England)|February 20, 2024
Fast and scalable querying of eukaryotic linear motifs with gget elmLaura Luebbert, Chi Hoang, Manjeet Kumar, et al.
Plos Genetics|December 20, 2018
Expression reflects population structureBrielin C Brown, Nicolas L Bray, Lior Pachter
Statistical Applications in Genetics and Molecular Biology|September 4, 2007
The cyclohedron test for finding periodic genes in time course expression studiesJason Morton, Lior Pachter, Anne Shiu, et al.
Genome Biology|June 9, 2021
BUTTERFLY: addressing the pooled amplification paradox with unique molecular identifiers in single-cell RNA-seqJohan Gustafsson, Jonathan Robinson, Jens Nielsen, et al.
Bioinformatics (Oxford, England)|March 17, 2020
Interpretable factor models of single-cell RNA-seq via variational autoencodersValentine Svensson, Adam Gayoso, Nir Yosef, et al.
Statistical Applications in Genetics and Molecular Biology|October 24, 2012
Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chainsMeromit Singer, Alexander Engström, Alexander Schönhuth, et al.
Plos Computational Biology|September 12, 2022
RNA velocity unraveledGennady Gorin, Meichen Fang, Tara Chari, et al.
Bioinformatics (Oxford, England)|June 24, 2011
Identification of novel transcripts in annotated genomes using RNA-SeqAdam Roberts, Harold Pimentel, Cole Trapnell, et al.
Elife|June 14, 2018
Association mapping from sequencing reads using <i>k</i>-mersAtif Rahman, Ingileif Hallgrímsdóttir, Michael Eisen, et al.
Pageof 20

Showing results (81-90 of 200) with videos related to

Sort By:
Pageof 20
Nature Methods|January 22, 2019
A discriminative learning approach to differential expression analysis for single-cell RNA-seqVasilis Ntranos, Lynn Yi, Páll Melsted, et al.
Bioinformatics (Oxford, England)|February 20, 2024
Fast and scalable querying of eukaryotic linear motifs with gget elmLaura Luebbert, Chi Hoang, Manjeet Kumar, et al.
Plos Genetics|December 20, 2018
Expression reflects population structureBrielin C Brown, Nicolas L Bray, Lior Pachter
Statistical Applications in Genetics and Molecular Biology|September 4, 2007
The cyclohedron test for finding periodic genes in time course expression studiesJason Morton, Lior Pachter, Anne Shiu, et al.
Genome Biology|June 9, 2021
BUTTERFLY: addressing the pooled amplification paradox with unique molecular identifiers in single-cell RNA-seqJohan Gustafsson, Jonathan Robinson, Jens Nielsen, et al.
Bioinformatics (Oxford, England)|March 17, 2020
Interpretable factor models of single-cell RNA-seq via variational autoencodersValentine Svensson, Adam Gayoso, Nir Yosef, et al.
Statistical Applications in Genetics and Molecular Biology|October 24, 2012
Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chainsMeromit Singer, Alexander Engström, Alexander Schönhuth, et al.
Plos Computational Biology|September 12, 2022
RNA velocity unraveledGennady Gorin, Meichen Fang, Tara Chari, et al.
Bioinformatics (Oxford, England)|June 24, 2011
Identification of novel transcripts in annotated genomes using RNA-SeqAdam Roberts, Harold Pimentel, Cole Trapnell, et al.
Elife|June 14, 2018
Association mapping from sequencing reads using <i>k</i>-mersAtif Rahman, Ingileif Hallgrímsdóttir, Michael Eisen, et al.
Pageof 20