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Confidence measures for protein fold recognition
Author(s) -
I. Sommer,
Alexander Zien,
Niklas von Öhsen,
Ralf Zimmer,
Thomas Lengauer
Publication year - 2002
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/18.6.802
Subject(s) - threading (protein sequence) , computer science , sequence (biology) , confidence interval , set (abstract data type) , quality score , artificial intelligence , data mining , pattern recognition (psychology) , machine learning , statistics , mathematics , protein structure , biology , biochemistry , genetics , operations management , economics , programming language , metric (unit)
We present an extensive evaluation of different methods and criteria to detect remote homologs of a given protein sequence. We investigate two associated problems: first, to develop a sensitive searching method to identify possible candidates and, second, to assign a confidence to the putative candidates in order to select the best one. For searching methods where the score distributions are known, p-values are used as confidence measure with great success. For the cases where such theoretical backing is absent, we propose empirical approximations to p-values for searching procedures.

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