Towards an automatic classification of protein structural domains based on structural similarity |
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Authors: | Vichetra Sam Chin-Hsien Tai Jean Garnier Jean-Francois Gibrat Byungkook Lee Peter J Munson |
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Institution: | (1) Mathematical and Statistical Computing Laboratory, DCB, CIT, NIH, DHHS, Bethesda, MD, USA;(2) Laboratory of Molecular Biology, CCR, NCI, NIH, DHHS, Bethesda, MD, USA;(3) Laboratoire de Mathematique Informatique et Genome, INRA, Jouy-en-Josas, France |
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Abstract: | Background Formal classification of a large collection of protein structures aids the understanding of evolutionary relationships among
them. Classifications involving manual steps, such as SCOP and CATH, face the challenge of increasing volume of available
structures. Automatic methods such as FSSP or Dali Domain Dictionary, yield divergent classifications, for reasons not yet
fully investigated. One possible reason is that the pairwise similarity scores used in automatic classification do not adequately
reflect the judgments made in manual classification. Another possibility is the difference between manual and automatic classification
procedures. We explore the degree to which these two factors might affect the final classification. |
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