J Chem Inf Model - Enrichment analysis for discovering biological associations in phenotypic screens.

Tópicos

{ compound(1573) activ(1297) structur(1058) }
{ gene(2352) biolog(1181) express(1162) }
{ method(1969) cluster(1462) data(1082) }
{ data(2317) use(1299) case(1017) }
{ howev(809) still(633) remain(590) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ can(774) often(719) complex(702) }
{ studi(2440) review(1878) systemat(933) }
{ error(1145) method(1030) estim(1020) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ research(1085) discuss(1038) issu(1018) }
{ state(1844) use(1261) util(961) }
{ can(981) present(881) function(850) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ motion(1329) object(1292) video(1091) }
{ algorithm(1844) comput(1787) effici(935) }
{ design(1359) user(1324) use(1319) }
{ general(901) number(790) one(736) }
{ record(1888) medic(1808) patient(1693) }
{ cost(1906) reduc(1198) effect(832) }
{ first(2504) two(1366) second(1323) }
{ activ(1138) subject(705) human(624) }
{ health(1844) social(1437) communiti(874) }
{ use(1733) differ(960) four(931) }
{ decis(3086) make(1611) patient(1517) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ 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) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ 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) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ 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) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ 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

A phenotypic screen (PS) is used to identify compounds causing a desired phenotype in a complex biological system where mechanisms and targets are largely unknown. Deconvoluting the mechanism of action of actives and identification of relevant targets and pathways remains a formidable challenge. Current methods fail to use the rich information available regarding compounds and their targets in a systematic way for this deconvolution. We have developed an enrichment analysis algorithm to identify targets associated with the desired phenotype in a rigorous data-driven manner using actives and hundreds of thousands of inactives in a PS, as well as results of thousands of available legacy target-based screens in an institution. Our method quantifies association between the PS and targets while reducing sampling bias, which leads to identification of novel targets, additional chemical matter, and appropriate assays. Its use is illustrated using two examples from our laboratories: TRAIL and DNA fragmentation. Enrichment analysis of these PSs is discussed using both biological pathway analysis and known cell biology to demonstrate the value of our method. We believe this enrichment analysis method is an indispensable tool for the analysis of PSs.

Resumo Limpo

phenotyp screen ps use identifi compound caus desir phenotyp complex biolog system mechan target larg unknown deconvolut mechan action activ identif relev target pathway remain formid challeng current method fail use rich inform avail regard compound target systemat way deconvolut develop enrich analysi algorithm identifi target associ desir phenotyp rigor datadriven manner use activ hundr thousand inact ps well result thousand avail legaci targetbas screen institut method quantifi associ ps target reduc sampl bias lead identif novel target addit chemic matter appropri assay use illustr use two exampl laboratori trail dna fragment enrich analysi pss discuss use biolog pathway analysi known cell biolog demonstr valu method believ enrich analysi method indispens tool analysi pss

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