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Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural networks

โœ Scribed by Qicheng Ma; Gung-Wei Chirn; Richard Cai; Joseph D Szustakowski; NR Nirmala


Book ID
115000006
Publisher
BioMed Central
Year
2005
Tongue
English
Weight
321 KB
Volume
6
Category
Article
ISSN
1471-2105

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## Abstract To improve secondary structure predictions in protein sequences, the information residing in multiple sequence alignments of substituted but structurally related proteins is exploited. A database comprised of 70 protein families and a total of 2, 500 sequences, some of which were aligne