BiasViz: visualization of amino acid biased regions in protein alignments

Publikationstyp:
Zeitschriftenaufsatz
Metadaten:
Autoren
  • Matthew R Huska
  • Henrik Buschmann
  • Miguel A Andrade-Navarro
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000251197800019&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1093/bioinformatics/btm489
eISSN
1460-2059
Externe Identifier
  • Clarivate Analytics Document Solution ID: 234XM
  • PubMed Identifier: 17921493
ISSN
1367-4803
Ausgabe der Veröffentlichung
22
Zeitschrift
BIOINFORMATICS
Paginierung
3093 - 3094
Datum der Veröffentlichung
2007
Status
Published
Titel
BiasViz: visualization of amino acid biased regions in protein alignments
Sub types
  • Article
Ausgabe der Zeitschrift
23

Datenquelle: Web of Science (Lite)

Andere Metadatenquellen:
Abstract
<jats:title>Abstract</jats:title><jats:p>Summary: About a third of all protein sequences have at least one composition biased region (CBR). Such regions might act as linkers between protein domains but often confer specific binding to various molecules; therefore, their characterization in terms of their boundaries and over-represented residues is important. Analysis of CBRs in a particular sequence can be time consuming if several types of biases have to be explored and their position visualized. Assessment of the significance of the detected CBRs can be approached by comparison to homologous protein sequences. To assist this procedure, we have developed BiasViz, a tool that allows to graphically studying local amino acid composition in protein sequences of a multiple sequence alignment.</jats:p><jats:p>Availability: BiasViz java applet and source code can be accessed from http://biasviz.sourceforge.net</jats:p><jats:p>Contact:  matthuska@alumni.uwaterloo.ca</jats:p>
Autoren
  • Matthew R Huska
  • Henrik Buschmann
  • Miguel A Andrade-Navarro
DOI
10.1093/bioinformatics/btm489
eISSN
1367-4811
ISSN
1367-4803
Ausgabe der Veröffentlichung
22
Zeitschrift
Bioinformatics
Sprache
en
Online publication date
2007
Paginierung
3093 - 3094
Datum der Veröffentlichung
2007
Status
Published
Herausgeber
Oxford University Press (OUP)
Herausgeber URL
http://dx.doi.org/10.1093/bioinformatics/btm489
Datum der Datenerfassung
2023
Titel
BiasViz: visualization of amino acid biased regions in protein alignments
Ausgabe der Zeitschrift
23

Datenquelle: Crossref

Abstract
About a third of all protein sequences have at least one composition biased region (CBR). Such regions might act as linkers between protein domains but often confer specific binding to various molecules; therefore, their characterization in terms of their boundaries and over-represented residues is important. Analysis of CBRs in a particular sequence can be time consuming if several types of biases have to be explored and their position visualized. Assessment of the significance of the detected CBRs can be approached by comparison to homologous protein sequences. To assist this procedure, we have developed BiasViz, a tool that allows to graphically studying local amino acid composition in protein sequences of a multiple sequence alignment.
Addresses
  • Molecular Medicine, Ottawa Health Research Institute, 501 Smyth Road, Ottawa, ON, Canada. matthuska@alumni.uwaterloo.ca
Autoren
  • Matthew R Huska
  • Henrik Buschmann
  • Miguel A Andrade-Navarro
DOI
10.1093/bioinformatics/btm489
eISSN
1367-4811
Externe Identifier
  • PubMed Identifier: 17921493
Open access
false
ISSN
1367-4803
Ausgabe der Veröffentlichung
22
Zeitschrift
Bioinformatics (Oxford, England)
Schlüsselwörter
  • Amino Acids
  • Proteins
  • Sequence Alignment
  • Sequence Analysis, Protein
  • Amino Acid Sequence
  • Protein Structure, Tertiary
  • Algorithms
  • Computer Graphics
  • Software
  • User-Computer Interface
  • Molecular Sequence Data
Sprache
eng
Medium
Print-Electronic
Online publication date
2007
Paginierung
3093 - 3094
Datum der Veröffentlichung
2007
Status
Published
Datum der Datenerfassung
2007
Titel
BiasViz: visualization of amino acid biased regions in protein alignments.
Sub types
  • Research Support, Non-U.S. Gov't
  • Journal Article
Ausgabe der Zeitschrift
23

Datenquelle: Europe PubMed Central

Abstract
About a third of all protein sequences have at least one composition biased region (CBR). Such regions might act as linkers between protein domains but often confer specific binding to various molecules; therefore, their characterization in terms of their boundaries and over-represented residues is important. Analysis of CBRs in a particular sequence can be time consuming if several types of biases have to be explored and their position visualized. Assessment of the significance of the detected CBRs can be approached by comparison to homologous protein sequences. To assist this procedure, we have developed BiasViz, a tool that allows to graphically studying local amino acid composition in protein sequences of a multiple sequence alignment.
Autoren
  • Matthew R Huska
  • Henrik Buschmann
  • Miguel A Andrade-Navarro
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/17921493
DOI
10.1093/bioinformatics/btm489
eISSN
1367-4811
Ausgabe der Veröffentlichung
22
Zeitschrift
Bioinformatics
Schlüsselwörter
  • Algorithms
  • Amino Acid Sequence
  • Amino Acids
  • Computer Graphics
  • Molecular Sequence Data
  • Protein Structure, Tertiary
  • Proteins
  • Sequence Alignment
  • Sequence Analysis, Protein
  • Software
  • User-Computer Interface
Sprache
eng
Country
England
Paginierung
3093 - 3094
PII
btm489
Datum der Veröffentlichung
2007
Status
Published
Datum, an dem der Datensatz öffentlich gemacht wurde
2007
Titel
BiasViz: visualization of amino acid biased regions in protein alignments.
Sub types
  • Journal Article
  • Research Support, Non-U.S. Gov't
Ausgabe der Zeitschrift
23

Datenquelle: PubMed

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