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A new method for analyzing protein sequence relationships based on Sammon maps
Author(s) -
Agrafiotis Dimitris K.
Publication year - 1997
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1002/pro.5560060203
Subject(s) - computer science , representation (politics) , similarity (geometry) , computational biology , simple (philosophy) , sequence (biology) , artificial intelligence , pattern recognition (psychology) , protein superfamily , sequence alignment , alignment free sequence analysis , biology , genetics , peptide sequence , gene , image (mathematics) , philosophy , epistemology , politics , political science , law
Abstract Recent advances in gene sequencing and rational drug design have re‐emphasized the need for new methods for protein analysis, classification, and structure and function prediction. In this article, we introduce a new method for analyzing protein sequences based on Sammon's non‐linear mapping algorithm. When applied to a family of homologous sequences, the method is able to capture the essential features of the similarity matrix, and provides a faithful representation of chemical or evolutionary distance in a simple and intuitive way. The merits of the new algorithm are demonstrated using examples from the protein kinase family.