Comput Math Methods Med - Na?ve Bayes classifier with feature selection to identify phage virion proteins.

Tópicos

{ sequenc(1873) structur(1644) protein(1328) }
{ method(2212) result(1239) propos(1039) }
{ imag(1057) registr(996) error(939) }
{ featur(3375) classif(2383) classifi(1994) }
{ assess(1506) score(1403) qualiti(1306) }
{ method(1557) propos(1049) approach(1037) }
{ detect(2391) sensit(1101) algorithm(908) }
{ featur(1941) imag(1645) propos(1176) }
{ perform(1367) use(1326) method(1137) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ method(1219) similar(1157) match(930) }
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{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ algorithm(1844) comput(1787) effici(935) }
{ model(2220) cell(1177) simul(1124) }
{ method(984) reconstruct(947) comput(926) }
{ data(3963) clinic(1234) research(1004) }
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{ state(1844) use(1261) util(961) }
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{ age(1611) year(1155) adult(843) }
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{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
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{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
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{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }

Resumo

Knowledge about the protein composition of phage virions is a key step to understand the functions of phage virion proteins. However, the experimental method to identify virion proteins is time consuming and expensive. Thus, it is highly desirable to develop novel computational methods for phage virion protein identification. In this study, a Na?ve Bayes based method was proposed to predict phage virion proteins using amino acid composition and dipeptide composition. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In the jackknife test, the proposed method achieved an accuracy of 79.15% for phage virion and nonvirion proteins classification, which are superior to that of other state-of-the-art classifiers. These results indicate that the proposed method could be as an effective and promising high-throughput method in phage proteomics research.

Resumo Limpo

knowledg protein composit phage virion key step understand function phage virion protein howev experiment method identifi virion protein time consum expens thus high desir develop novel comput method phage virion protein identif studi nave bay base method propos predict phage virion protein use amino acid composit dipeptid composit order remov redund inform novel featur select techniqu employ singl optim featur jackknif test propos method achiev accuraci phage virion nonvirion protein classif superior stateoftheart classifi result indic propos method effect promis highthroughput method phage proteom research

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