Model-based prediction of sequence alignment quality | Zendy

Virpi Ahola | Zendy; Tero Aittokallio | Zendy; Mauno Vihinen | Zendy; Esa Uusipaikka | Zendy

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Model-based prediction of sequence alignment quality

Author(s) -

Virpi Ahola,

Tero Aittokallio,

Mauno Vihinen,

Esa Uusipaikka

Publication year - 2008

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/btn414

Subject(s) - multiple sequence alignment , quality score , computer science , reliability (semiconductor) , sequence (biology) , sequence alignment , set (abstract data type) , quality (philosophy) , data mining , measure (data warehouse) , score , statistics , mathematics , machine learning , biology , genetics , peptide sequence , metric (unit) , power (physics) , operations management , physics , philosophy , epistemology , quantum mechanics , gene , economics , programming language

Multiple sequence alignment (MSA) is an essential prerequisite for many sequence analysis methods and valuable tool itself for describing relationships between protein sequences. Since the success of the sequence analysis is highly dependent on the reliability of alignments, measures for assessing the quality of alignments are highly requisite.

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