Comput Biol Chem - Subgrouping Automata: automatic sequence subgrouping using phylogenetic tree-based optimum subgrouping algorithm.

Tópicos

{ sequenc(1873) structur(1644) protein(1328) }
{ structur(1116) can(940) graph(676) }
{ error(1145) method(1030) estim(1020) }
{ system(1976) rule(880) can(841) }
{ signal(2180) analysi(812) frequenc(800) }
{ use(976) code(926) identifi(902) }
{ can(981) present(881) function(850) }
{ drug(1928) target(777) effect(648) }
{ imag(2830) propos(1344) filter(1198) }
{ algorithm(1844) comput(1787) effici(935) }
{ perform(1367) use(1326) method(1137) }
{ imag(1057) registr(996) error(939) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ extract(1171) text(1153) clinic(932) }
{ design(1359) user(1324) use(1319) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ risk(3053) factor(974) diseas(938) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ studi(1119) effect(1106) posit(819) }
{ health(3367) inform(1360) care(1135) }
{ research(1218) medic(880) student(794) }
{ data(2317) use(1299) case(1017) }
{ first(2504) two(1366) second(1323) }
{ use(1733) differ(960) four(931) }
{ method(1969) cluster(1462) data(1082) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ bind(1733) structur(1185) ligand(1036) }
{ method(1219) similar(1157) match(930) }
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{ network(2748) neural(1063) input(814) }
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{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
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{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
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{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ 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(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Sequence subgrouping for a given sequence set can enable various informative tasks such as the functional discrimination of sequence subsets and the functional inference of unknown sequences. Because an identity threshold for sequence subgrouping may vary according to the given sequence set, it is highly desirable to construct a robust subgrouping algorithm which automatically identifies an optimal identity threshold and generates subgroups for a given sequence set. To meet this end, an automatic sequence subgrouping method, named 'Subgrouping Automata' was constructed. Firstly, tree analysis module analyzes the structure of tree and calculates the all possible subgroups in each node. Sequence similarity analysis module calculates average sequence similarity for all subgroups in each node. Representative sequence generation module finds a representative sequence using profile analysis and self-scoring for each subgroup. For all nodes, average sequence similarities are calculated and 'Subgrouping Automata' searches a node showing statistically maximum sequence similarity increase using Student's t-value. A node showing the maximum t-value, which gives the most significant differences in average sequence similarity between two adjacent nodes, is determined as an optimum subgrouping node in the phylogenetic tree. Further analysis showed that the optimum subgrouping node from SA prevents under-subgrouping and over-subgrouping.

Resumo Limpo

sequenc subgroup given sequenc set can enabl various inform task function discrimin sequenc subset function infer unknown sequenc ident threshold sequenc subgroup may vari accord given sequenc set high desir construct robust subgroup algorithm automat identifi optim ident threshold generat subgroup given sequenc set meet end automat sequenc subgroup method name subgroup automata construct first tree analysi modul analyz structur tree calcul possibl subgroup node sequenc similar analysi modul calcul averag sequenc similar subgroup node repres sequenc generat modul find repres sequenc use profil analysi selfscor subgroup node averag sequenc similar calcul subgroup automata search node show statist maximum sequenc similar increas use student tvalu node show maximum tvalu give signific differ averag sequenc similar two adjac node determin optimum subgroup node phylogenet tree analysi show optimum subgroup node sa prevent undersubgroup oversubgroup

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