Partner-aware prediction of interacting residues in protein-protein complexes from sequence data

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Partner-aware prediction of interacting residues in protein-protein complexes from sequence data is …
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scholarly articleQ13442814

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P819ADS bibcode2011PLoSO...629104A
P356DOI10.1371/JOURNAL.PONE.0029104
P932PMC publication ID3237601
P698PubMed publication ID22194998
P5875ResearchGate publication ID51921113

P50authorKenji MizuguchiQ57025667
Shandar AhmadQ46803664
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Applying the Naïve Bayes classifier with kernel density estimation to the prediction of protein-protein interaction sites.Q48204770
Prediction of protein-protein interactions using random decision forest frameworkQ48470497
Prediction of protein interaction sites from sequence profile and residue neighbor listQ49265986
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue12
P407language of work or nameEnglishQ1860
P304page(s)e29104
P577publication date2011-12-14
P1433published inPLOS OneQ564954
P1476titlePartner-aware prediction of interacting residues in protein-protein complexes from sequence data
P478volume6

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cites work (P2860)
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Q45943660Different protein-protein interface patterns predicted by different machine learning methods.
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Q91638839βC1, pathogenicity determinant encoded by Cotton leaf curl Multan betasatellite, interacts with calmodulin-like protein 11 (Gh-CML11) in Gossypium hirsutum

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