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Nanjiang Shu

Showing results (1-10 of 13) with videos related to

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Bioinformatics (Oxford, England)|April 21, 2011
KalignP: improved multiple sequence alignments using position specific gap penalties in Kalign2Nanjiang Shu, Arne Elofsson
Bioinformatics (Oxford, England)|December 17, 2009
A novel method for accurate one-dimensional protein structure prediction based on fragment matchingTuping Zhou, Nanjiang Shu, Sven Hovmöller
Bioinformatics (Oxford, England)|February 5, 2008
Prediction of zinc-binding sites in proteins from sequenceNanjiang Shu, Tuping Zhou, Sven Hovmöller
Current Protein & Peptide Science|August 12, 2008
Describing and comparing protein structures using shape stringsNanjiang Shu, Sven Hovmöller, Tuping Zhou
Scientific Reports|October 5, 2016
ProQ3: Improved model quality assessments using Rosetta energy termsKarolis Uziela, Nanjiang Shu, Björn Wallner, et al.
Bioinformatics (Oxford, England)|December 9, 2015
Improved topology prediction using the terminal hydrophobic helices ruleChristoph Peters, Konstantinos D Tsirigos, Nanjiang Shu, et al.
Bioinformatics (Oxford, England)|January 23, 2016
Inclusion of dyad-repeat pattern improves topology prediction of transmembrane β-barrel proteinsSikander Hayat, Christoph Peters, Nanjiang Shu, et al.
Nucleic Acids Research|May 14, 2015
The TOPCONS web server for consensus prediction of membrane protein topology and signal peptidesKonstantinos D Tsirigos, Christoph Peters, Nanjiang Shu, et al.
Proteins|March 11, 2018
Improved protein model quality assessments by changing the target functionKarolis Uziela, David Menéndez Hurtado, Nanjiang Shu, et al.
Bioinformatics (Oxford, England)|January 6, 2017
ProQ3D: improved model quality assessments using deep learningKarolis Uziela, David Menéndez Hurtado, Nanjiang Shu, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|April 21, 2011
KalignP: improved multiple sequence alignments using position specific gap penalties in Kalign2Nanjiang Shu, Arne Elofsson
Bioinformatics (Oxford, England)|December 17, 2009
A novel method for accurate one-dimensional protein structure prediction based on fragment matchingTuping Zhou, Nanjiang Shu, Sven Hovmöller
Bioinformatics (Oxford, England)|February 5, 2008
Prediction of zinc-binding sites in proteins from sequenceNanjiang Shu, Tuping Zhou, Sven Hovmöller
Current Protein & Peptide Science|August 12, 2008
Describing and comparing protein structures using shape stringsNanjiang Shu, Sven Hovmöller, Tuping Zhou
Scientific Reports|October 5, 2016
ProQ3: Improved model quality assessments using Rosetta energy termsKarolis Uziela, Nanjiang Shu, Björn Wallner, et al.
Bioinformatics (Oxford, England)|December 9, 2015
Improved topology prediction using the terminal hydrophobic helices ruleChristoph Peters, Konstantinos D Tsirigos, Nanjiang Shu, et al.
Bioinformatics (Oxford, England)|January 23, 2016
Inclusion of dyad-repeat pattern improves topology prediction of transmembrane β-barrel proteinsSikander Hayat, Christoph Peters, Nanjiang Shu, et al.
Nucleic Acids Research|May 14, 2015
The TOPCONS web server for consensus prediction of membrane protein topology and signal peptidesKonstantinos D Tsirigos, Christoph Peters, Nanjiang Shu, et al.
Proteins|March 11, 2018
Improved protein model quality assessments by changing the target functionKarolis Uziela, David Menéndez Hurtado, Nanjiang Shu, et al.
Bioinformatics (Oxford, England)|January 6, 2017
ProQ3D: improved model quality assessments using deep learningKarolis Uziela, David Menéndez Hurtado, Nanjiang Shu, et al.
Pageof 2