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Bioinformatics
Article . 1998 . Peer-reviewed
Data sources: Crossref
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Bioinformatics
Article
Data sources: UnpayWall
Bioinformatics
Article . 1998
DBLP
Article . 2020
Data sources: DBLP
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SSMAL: similarity searching with alignment graphs.

Authors: Pierre Nicodème;

SSMAL: similarity searching with alignment graphs.

Abstract

Abstract MOTIVATION: We want to provide biologists with a fast and sensitive scanning tool for searching local alignments of a protein query sequence against databases of protein multiple alignments, such as ProDom. Conversely, we want to provide a tool for locally aligning a protein multiple alignment query against a protein database such as SWISSPROT. RESULTS: We developed the program SSMAL (Shuffling Similarities with Multiple Alignments) which utilizes features of the Blast (Altschul et al., J. Mol. Biol., 215, 403-410, 1990) algorithm and part of the Blast code. Our software allows both scanning of multiple alignments and searching with a multiple alignment. Deletions in the multiple alignment only are handled and a SSMAL search may miss some similarities found by a profile search. However, an SSMAL scan of a database such as ProDom would be 20-30 times faster that a profile scan. In the worst case, a SSMAL search is approximately 9 times faster than a profile search. AVAILABILITY: http://www.dkfz-heidelberg.de/tbi/ people/nicodeme and follow the hyperlink SSMAL. CONTACT: p.nicodeme@DKFZ-Heidelberg.de

Related Organizations
Keywords

Databases, Factual, Molecular Sequence Data, Computational Biology, Proteins, Models, Theoretical, Globins, Animals, Humans, Amino Acid Sequence, Sequence Alignment, Conserved Sequence, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Top 10%
gold