Methods and algorithms for statistical analysis of protein sequences.

Volker Brendel(Stanford University), Philipp Bücher(Stanford University), Illiah Nourbakhsh(Stanford University), B. Edwin Blaisdell(Stanford University), Samuel Karlin(Stanford University)
Proceedings of the National Academy of Sciences
March 15, 1992
Cited by 386Open Access
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Abstract

We describe several protein sequence statistics designed to evaluate distinctive attributes of residue content and arrangement in primary structure. Considered are global compositional biases, local clustering of different residue types (e.g., charged residues, hydrophobic residues, Ser/Thr), long runs of charged or uncharged residues, periodic patterns, counts and distribution of homooligopeptides, and unusual spacings between particular residue types. The computer program SAPS (statistical analysis of protein sequences) calculates all the statistics for any individual protein sequence input and is available for the UNIX environment through electronic mail on request to V.B. (volker/genomic@stanford.edu).


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