Comput Biol Chem - newDNA-Prot: Prediction of DNA-binding proteins by employing support vector machine and a comprehensive sequence representation.

Tópicos

{ featur(3375) classif(2383) classifi(1994) }
{ method(2212) result(1239) propos(1039) }
{ sequenc(1873) structur(1644) protein(1328) }
{ analysi(2126) use(1163) compon(1037) }
{ model(2341) predict(2261) use(1141) }
{ state(1844) use(1261) util(961) }
{ group(2977) signific(1463) compar(1072) }
{ gene(2352) biolog(1181) express(1162) }
{ import(1318) role(1303) understand(862) }
{ imag(1947) propos(1133) code(1026) }
{ care(1570) inform(1187) nurs(1089) }
{ spatial(1525) area(1432) region(1030) }
{ health(3367) inform(1360) care(1135) }
{ imag(2675) segment(2577) method(1081) }
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{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ data(1714) softwar(1251) tool(1186) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ compound(1573) activ(1297) structur(1058) }
{ ehr(2073) health(1662) electron(1139) }
{ cost(1906) reduc(1198) effect(832) }
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{ time(1939) patient(1703) rate(768) }
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{ estim(2440) model(1874) function(577) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Identification of DNA-binding proteins is essential in studying cellular activities as the DNA-binding proteins play a pivotal role in gene regulation. In this study, we propose newDNA-Prot, a DNA-binding protein predictor that employs support vector machine classifier and a comprehensive feature representation. The sequence representation are categorized into 6 groups: primary sequence based, evolutionary profile based, predicted secondary structure based, predicted relative solvent accessibility based, physicochemical property based and biological function based features. The mRMR, wrapper and two-stage feature selection methods are employed for removing irrelevant features and reducing redundant features. Experiments demonstrate that the two-stage method performs better than the mRMR and wrapper methods. We also perform a statistical analysis on the selected features and results show that more than 95% of the selected features are statistically significant and they cover all 6 feature groups. The newDNA-Prot method is compared with several state of the art algorithms, including iDNA-Prot, DNAbinder and DNA-Prot. The results demonstrate that newDNA-Prot method outperforms the iDNA-Prot, DNAbinder and DNA-Prot methods. More specific, newDNA-Prot improves the runner-up method, DNA-Prot for around 10% on several evaluation measures. The proposed newDNA-Prot method is available at http://sourceforge.net/projects/newdnaprot/

Resumo Limpo

identif dnabind protein essenti studi cellular activ dnabind protein play pivot role gene regul studi propos newdnaprot dnabind protein predictor employ support vector machin classifi comprehens featur represent sequenc represent categor group primari sequenc base evolutionari profil base predict secondari structur base predict relat solvent access base physicochem properti base biolog function base featur mrmr wrapper twostag featur select method employ remov irrelev featur reduc redund featur experi demonstr twostag method perform better mrmr wrapper method also perform statist analysi select featur result show select featur statist signific cover featur group newdnaprot method compar sever state art algorithm includ idnaprot dnabind dnaprot result demonstr newdnaprot method outperform idnaprot dnabind dnaprot method specif newdnaprot improv runnerup method dnaprot around sever evalu measur propos newdnaprot method avail httpsourceforgenetprojectsnewdnaprot

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