METHODS AND ALGORITHMS FOR STATISTICAL-ANALYSIS OF PROTEIN SEQUENCES

被引:335
作者
BRENDEL, V
BUCHER, P
NOURBAKHSH, IR
BLAISDELL, BE
KARLIN, S
机构
[1] Department of Mathematics, Stanford University, Stanford
[2] Inst. Suisse de Rech. E., CH-1066 Épalinges s/Lausanne
关键词
CHARGE CLUSTER; MULTIPLET; PROTEIN PERIODICITIES; RESIDUE SPACINGS; SAPS;
D O I
10.1073/pnas.89.6.2002
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页码:2002 / 2006
页数:5
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