J Integr Bioinform - Integrating sequence analysis with biophysical modelling for accurate transcription start site prediction.

Tópicos

{ gene(2352) biolog(1181) express(1162) }
{ sequenc(1873) structur(1644) protein(1328) }
{ detect(2391) sensit(1101) algorithm(908) }
{ problem(2511) optim(1539) algorithm(950) }
{ research(1085) discuss(1038) issu(1018) }
{ health(1844) social(1437) communiti(874) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ data(1714) softwar(1251) tool(1186) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ imag(2830) propos(1344) filter(1198) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ framework(1458) process(801) describ(734) }
{ algorithm(1844) comput(1787) effici(935) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ sampl(1606) size(1419) use(1276) }
{ data(3008) multipl(1320) sourc(1022) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ implement(1333) system(1263) develop(1122) }
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{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
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{ general(901) number(790) one(736) }
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{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ 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) }
{ method(2212) result(1239) propos(1039) }

Resumo

Promoter prediction in bacteria is a classical bioinformatics problem, where available methods for regulatory element detection exhibit a very high number of false positives. We here argue that accurate transcription start site (TSS) prediction is a complex problem, where available methods for sequence motif discovery are not in itself well adopted for solving the problem. We here instead propose that the problem requires integration of quantitative understanding of transcription initiation with careful description of promoter sequence specificity. We review evidence for this viewpoint, and discuss a current progress on these issues on the example of sigma70 transcription start sites in E. coli.

Resumo Limpo

promot predict bacteria classic bioinformat problem avail method regulatori element detect exhibit high number fals posit argu accur transcript start site tss predict complex problem avail method sequenc motif discoveri well adopt solv problem instead propos problem requir integr quantit understand transcript initi care descript promot sequenc specif review evid viewpoint discuss current progress issu exampl sigma transcript start site e coli

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