J. Comput. Biol. - Simultaneous alignment and folding of protein sequences.

Tópicos

{ sequenc(1873) structur(1644) protein(1328) }
{ algorithm(1844) comput(1787) effici(935) }
{ can(774) often(719) complex(702) }
{ howev(809) still(633) remain(590) }
{ chang(1828) time(1643) increas(1301) }
{ method(984) reconstruct(947) comput(926) }
{ cost(1906) reduc(1198) effect(832) }
{ analysi(2126) use(1163) compon(1037) }
{ method(1969) cluster(1462) data(1082) }
{ clinic(1479) use(1117) guidelin(835) }
{ control(1307) perform(991) simul(935) }
{ perform(999) metric(946) measur(919) }
{ compound(1573) activ(1297) structur(1058) }
{ model(2656) set(1616) predict(1553) }
{ data(1737) use(1416) pattern(1282) }
{ bind(1733) structur(1185) ligand(1036) }
{ featur(3375) classif(2383) classifi(1994) }
{ treatment(1704) effect(941) patient(846) }
{ framework(1458) process(801) describ(734) }
{ design(1359) user(1324) use(1319) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ model(2341) predict(2261) use(1141) }
{ studi(1119) effect(1106) posit(819) }
{ spatial(1525) area(1432) region(1030) }
{ data(2317) use(1299) case(1017) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ can(981) present(881) function(850) }
{ process(1125) use(805) approach(778) }
{ detect(2391) sensit(1101) algorithm(908) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ method(1219) similar(1157) match(930) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ search(2224) databas(1162) retriev(909) }
{ data(3963) clinic(1234) research(1004) }
{ risk(3053) factor(974) diseas(938) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ 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) }
{ health(1844) social(1437) communiti(874) }
{ 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) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ activ(1452) weight(1219) physic(1104) }
{ method(2212) result(1239) propos(1039) }

Resumo

Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We present partiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm's complexity is polynomial in time and space. Algorithmically, partiFold-Align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. We demonstrate the efficacy of these techniques on transmembrane ?-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. Testing against structurally derived sequence alignments, partiFold-Align significantly outperforms state-of-the-art pairwise and multiple sequence alignment tools in the most difficult low-sequence homology case. It also improves secondary structure prediction where current approaches fail. Importantly, partiFold-Align requires no prior training. These general techniques are widely applicable to many more protein families (partiFold-Align is available at http://partifold.csail.mit.edu/ ).

Resumo Limpo

accur compar analysi tool lowhomolog protein remain difficult challeng comput biolog especi sequenc align consensus fold problem present partifoldalign first algorithm simultan align consensus fold unalign protein sequenc algorithm complex polynomi time space algorithm partifoldalign exploit sparsiti set supersecondari structur pair align candid achiev effect cubic run time simultan pairwis align fold demonstr efficaci techniqu transmembran barrel protein import yet difficult class protein known threedimension structur test structur deriv sequenc align partifoldalign signific outperform stateoftheart pairwis multipl sequenc align tool difficult lowsequ homolog case also improv secondari structur predict current approach fail import partifoldalign requir prior train general techniqu wide applic mani protein famili partifoldalign avail httppartifoldcsailmitedu

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