CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction
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Title
CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction
Authors
Keywords
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Journal
BIOINFORMATICS
Volume 32, Issue 12, Pages i332-i340
Publisher
Oxford University Press (OUP)
Online
2016-06-15
DOI
10.1093/bioinformatics/btw271
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- (2012) N. M. Daniels et al. BIOINFORMATICS
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- (2012) Debora S Marks et al. NATURE BIOTECHNOLOGY
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- (2012) Morten Källberg et al. Nature Protocols
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- (2008) Sitao Wu et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
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