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SPAAN: a software program for prediction of adhesins and adhesin-like proteins using neural networks.

Identifieur interne : 000046 ( Ncbi/Merge ); précédent : 000045; suivant : 000047

SPAAN: a software program for prediction of adhesins and adhesin-like proteins using neural networks.

Auteurs : Gaurav Sachdeva [Inde] ; Kaushal Kumar ; Preti Jain ; Srinivasan Ramachandran

Source :

RBID : pubmed:15374866

Descripteurs français

English descriptors

Abstract

The adhesion of microbial pathogens to host cells is mediated by adhesins. Experimental methods used for characterizing adhesins are time-consuming and demand large resources. The availability of specialized software can rapidly aid experimenters in simplifying this problem. We have employed 105 compositional properties and artificial neural networks to develop SPAAN, which predicts the probability of a protein being an adhesin (Pad).

DOI: 10.1093/bioinformatics/bti028
PubMed: 15374866

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pubmed:15374866

Le document en format XML

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<title xml:lang="en">SPAAN: a software program for prediction of adhesins and adhesin-like proteins using neural networks.</title>
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<name sortKey="Sachdeva, Gaurav" sort="Sachdeva, Gaurav" uniqKey="Sachdeva G" first="Gaurav" last="Sachdeva">Gaurav Sachdeva</name>
<affiliation wicri:level="1">
<nlm:affiliation>G.N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology Mall Road, Delhi 110 007, India.</nlm:affiliation>
<country xml:lang="fr">Inde</country>
<wicri:regionArea>G.N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology Mall Road, Delhi 110 007</wicri:regionArea>
<wicri:noRegion>Delhi 110 007</wicri:noRegion>
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<name sortKey="Kumar, Kaushal" sort="Kumar, Kaushal" uniqKey="Kumar K" first="Kaushal" last="Kumar">Kaushal Kumar</name>
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<name sortKey="Jain, Preti" sort="Jain, Preti" uniqKey="Jain P" first="Preti" last="Jain">Preti Jain</name>
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<name sortKey="Ramachandran, Srinivasan" sort="Ramachandran, Srinivasan" uniqKey="Ramachandran S" first="Srinivasan" last="Ramachandran">Srinivasan Ramachandran</name>
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<term>Adhesins, Bacterial (chemistry)</term>
<term>Adhesins, Bacterial (metabolism)</term>
<term>Algorithms</term>
<term>Animals</term>
<term>Humans</term>
<term>Models, Biological</term>
<term>Models, Chemical</term>
<term>Models, Statistical</term>
<term>Neural Networks, Computer</term>
<term>Protein Isoforms (chemistry)</term>
<term>Protein Isoforms (metabolism)</term>
<term>Sequence Alignment (methods)</term>
<term>Sequence Analysis, Protein (methods)</term>
<term>Sequence Homology, Amino Acid</term>
<term>Software</term>
<term>Structure-Activity Relationship</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr">
<term>Adhésines bactériennes ()</term>
<term>Adhésines bactériennes (métabolisme)</term>
<term>Algorithmes</term>
<term>Alignement de séquences ()</term>
<term>Analyse de séquence de protéine ()</term>
<term>Animaux</term>
<term>Humains</term>
<term>Isoformes de protéines ()</term>
<term>Isoformes de protéines (métabolisme)</term>
<term>Logiciel</term>
<term>Modèles biologiques</term>
<term>Modèles chimiques</term>
<term>Modèles statistiques</term>
<term>Relation structure-activité</term>
<term>Similitude de séquences d'acides aminés</term>
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<keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en">
<term>Adhesins, Bacterial</term>
<term>Protein Isoforms</term>
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<keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en">
<term>Adhesins, Bacterial</term>
<term>Protein Isoforms</term>
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<term>Sequence Alignment</term>
<term>Sequence Analysis, Protein</term>
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<term>Adhésines bactériennes</term>
<term>Isoformes de protéines</term>
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<term>Algorithmes</term>
<term>Alignement de séquences</term>
<term>Analyse de séquence de protéine</term>
<term>Animaux</term>
<term>Humains</term>
<term>Isoformes de protéines</term>
<term>Logiciel</term>
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<term>Modèles chimiques</term>
<term>Modèles statistiques</term>
<term>Relation structure-activité</term>
<term>Similitude de séquences d'acides aminés</term>
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<front>
<div type="abstract" xml:lang="en">The adhesion of microbial pathogens to host cells is mediated by adhesins. Experimental methods used for characterizing adhesins are time-consuming and demand large resources. The availability of specialized software can rapidly aid experimenters in simplifying this problem. We have employed 105 compositional properties and artificial neural networks to develop SPAAN, which predicts the probability of a protein being an adhesin (Pad).</div>
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<Year>2019</Year>
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<Volume>21</Volume>
<Issue>4</Issue>
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<Month>Feb</Month>
<Day>15</Day>
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<AbstractText Label="MOTIVATION" NlmCategory="BACKGROUND">The adhesion of microbial pathogens to host cells is mediated by adhesins. Experimental methods used for characterizing adhesins are time-consuming and demand large resources. The availability of specialized software can rapidly aid experimenters in simplifying this problem. We have employed 105 compositional properties and artificial neural networks to develop SPAAN, which predicts the probability of a protein being an adhesin (Pad).</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">SPAAN had optimal sensitivity of 89% and specificity of 100% on a defined test set and could identify 97.4% of known adhesins at high Pad value from a wide range of bacteria. Furthermore, SPAAN facilitated improved annotation of several proteins as adhesins. Novel adhesins were identified in 17 pathogenic organisms causing diseases in humans and plants. In the severe acute respiratory syndrome (SARS) associated human corona virus, the spike glycoprotein and nsps (nsp2, nsp5, nsp6 and nsp7) were identified as having adhesin-like characteristics. These results offer new lead for rapid experimental testing.</AbstractText>
<AbstractText Label="AVAILABILITY" NlmCategory="BACKGROUND">SPAAN is freely available through ftp://203.195.151.45</AbstractText>
<AbstractText Label="CONTACT" NlmCategory="BACKGROUND">ramu@igib.res.in.</AbstractText>
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