caa a22 4500 378925962 CHVBK 20180305123617.0 cr unu---uuuuu 161128e20041030xx s 000 0 eng 10.2202/1544-6115.1074 doi (NATIONALLICENCE)gruyter-10.2202/1544-6115.1074 Statistical Methods for Identifying Conserved Residues in Multiple Sequence Alignment [Elektronische Daten] [Virpi Ahola, Tero Aittokallio, Esa Uusipaikka, Mauno Vihinen] The assessment of residue conservation in a multiple sequence alignment is a central issue in bioinformatics. Conserved residues and regions are used to determine structural and functional motifs or evolutionary relationships between the sequences of a multiple sequence alignment. For this reason, residue conservation is a valuable measure for database and motif search or for estimating the quality of alignments. In this paper, we present statistical methods for identifying conserved residues in multiple sequence alignments. While most earlier studies examine the positional conservation of the alignment, we focus on the detection of individual conserved residues at a position. The major advantages of multiple comparison methods originate from their ability to select conserved residues simultaneously and to consider the variability of the residue estimates. Large-scale simulations were used for the comparative analysis of the methods. Practical performance was studied by comparing the structurally and functionally important residues of Src homology 2 (SH2) domains to the assignments of the conservation indices. The applicability of the indices was also compared in three additional protein families comprising different degrees of entropy and variability in alignment positions. The results indicate that statistical multiple comparison methods are sensitive and reliable in identifying conserved residues. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston Computational Biology/Bioinformatics nationallicence Protein sequence analysis nationallicence residue conservation nationallicence conservation index nationallicence multiple comparison nationallicence SH2 domain nationallicence Ahola Virpi University of Turku aut Aittokallio Tero University of Turku aut Uusipaikka Esa University of Turku aut Vihinen Mauno University of Tampere aut Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-10-30), 1-28 3:1<1 2004 3 sagmb https://doi.org/10.2202/1544-6115.1074 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1544-6115.1074 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ahola Virpi University of Turku aut NATIONALLICENCE 700 1- Aittokallio Tero University of Turku aut NATIONALLICENCE 700 1- Uusipaikka Esa University of Turku aut NATIONALLICENCE 700 1- Vihinen Mauno University of Tampere aut NATIONALLICENCE 773 0- Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-10-30), 1-28 3:1<1 2004 3 sagmb CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter