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Rob Egan

Showing results (1-10 of 14) with videos related to

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BMC Bioinformatics|November 8, 2019
De novo Nanopore read quality improvement using deep learningNathan LaPierre, Rob Egan, Wei Wang, et al.
Peerj|September 4, 2015
MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communitiesDongwan D Kang, Jeff Froula, Rob Egan, et al.
Bioinformatics (Oxford, England)|January 11, 2013
ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assembliesScott C Clark, Rob Egan, Peter I Frazier, et al.
BMC Bioinformatics|November 30, 2022
Persistent memory as an effective alternative to random access memory in metagenome assemblyJingchao Sun, Zhining Qiu, Rob Egan, et al.
Mbio|March 6, 2023
Genomic Features Predict Bacterial Life History Strategies in Soil, as Identified by Metagenomic Stable Isotope ProbingSamuel E Barnett, Rob Egan, Brian Foster, et al.
Peerj|August 8, 2019
MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assembliesDongwan D Kang, Feng Li, Edward Kirton, et al.
Peerj|September 27, 2023
Integrating chromatin conformation information in a self-supervised learning model improves metagenome binningHarrison Ho, Mansi Chovatia, Rob Egan, et al.
Nature Communications|October 13, 2017
Ecogenomics of virophages and their giant virus hosts assessed through time series metagenomicsSimon Roux, Leong-Keat Chan, Rob Egan, et al.
Scientific Reports|July 3, 2020
Terabase-scale metagenome coassembly with MetaHipMerSteven Hofmeyr, Rob Egan, Evangelos Georganas, et al.
Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|January 21, 2020
The parallelism motifs of genomic data analysisKatherine Yelick, Aydın Buluç, Muaaz Awan, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
BMC Bioinformatics|November 8, 2019
De novo Nanopore read quality improvement using deep learningNathan LaPierre, Rob Egan, Wei Wang, et al.
Peerj|September 4, 2015
MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communitiesDongwan D Kang, Jeff Froula, Rob Egan, et al.
Bioinformatics (Oxford, England)|January 11, 2013
ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assembliesScott C Clark, Rob Egan, Peter I Frazier, et al.
BMC Bioinformatics|November 30, 2022
Persistent memory as an effective alternative to random access memory in metagenome assemblyJingchao Sun, Zhining Qiu, Rob Egan, et al.
Mbio|March 6, 2023
Genomic Features Predict Bacterial Life History Strategies in Soil, as Identified by Metagenomic Stable Isotope ProbingSamuel E Barnett, Rob Egan, Brian Foster, et al.
Peerj|August 8, 2019
MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assembliesDongwan D Kang, Feng Li, Edward Kirton, et al.
Peerj|September 27, 2023
Integrating chromatin conformation information in a self-supervised learning model improves metagenome binningHarrison Ho, Mansi Chovatia, Rob Egan, et al.
Nature Communications|October 13, 2017
Ecogenomics of virophages and their giant virus hosts assessed through time series metagenomicsSimon Roux, Leong-Keat Chan, Rob Egan, et al.
Scientific Reports|July 3, 2020
Terabase-scale metagenome coassembly with MetaHipMerSteven Hofmeyr, Rob Egan, Evangelos Georganas, et al.
Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|January 21, 2020
The parallelism motifs of genomic data analysisKatherine Yelick, Aydın Buluç, Muaaz Awan, et al.
Pageof 2