Wiley Interdiscip Rev Syst Biol Med - Promise of personalized omics to precision medicine.

Tópicos

{ research(1085) discuss(1038) issu(1018) }
{ health(3367) inform(1360) care(1135) }
{ gene(2352) biolog(1181) express(1162) }
{ system(1976) rule(880) can(841) }
{ sequenc(1873) structur(1644) protein(1328) }
{ treatment(1704) effect(941) patient(846) }
{ case(1353) use(1143) diagnosi(1136) }
{ first(2504) two(1366) second(1323) }
{ use(2086) technolog(871) perceiv(783) }
{ can(774) often(719) complex(702) }
{ bind(1733) structur(1185) ligand(1036) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ extract(1171) text(1153) clinic(932) }
{ risk(3053) factor(974) diseas(938) }
{ record(1888) medic(1808) patient(1693) }
{ imag(1947) propos(1133) code(1026) }
{ measur(2081) correl(1212) valu(896) }
{ assess(1506) score(1403) qualiti(1306) }
{ framework(1458) process(801) describ(734) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ visual(1396) interact(850) tool(830) }
{ blood(1257) pressur(1144) flow(957) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ patient(2837) hospit(1953) medic(668) }
{ age(1611) year(1155) adult(843) }
{ sampl(1606) size(1419) use(1276) }
{ intervent(3218) particip(2042) group(1664) }
{ health(1844) social(1437) communiti(874) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ model(3404) distribut(989) bayesian(671) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ imag(1057) registr(996) error(939) }
{ 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) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ spatial(1525) area(1432) region(1030) }
{ model(3480) simul(1196) paramet(876) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ 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) }
{ use(1733) differ(960) four(931) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ decis(3086) make(1611) patient(1517) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The rapid development of high-throughput technologies and computational frameworks enables the examination of biological systems in unprecedented detail. The ability to study biological phenomena at omics levels in turn is expected to lead to significant advances in personalized and precision medicine. Patients can be treated according to their own molecular characteristics. Individual omes as well as the integrated profiles of multiple omes, such as the genome, the epigenome, the transcriptome, the proteome, the metabolome, the antibodyome, and other omics information are expected to be valuable for health monitoring, preventative measures, and precision medicine. Moreover, omics technologies have the potential to transform medicine from traditional symptom-oriented diagnosis and treatment of diseases toward disease prevention and early diagnostics. We discuss here the advances and challenges in systems biology-powered personalized medicine at its current stage, as well as a prospective view of future personalized health care at the end of this review.

Resumo Limpo

rapid develop highthroughput technolog comput framework enabl examin biolog system unpreced detail abil studi biolog phenomena omic level turn expect lead signific advanc person precis medicin patient can treat accord molecular characterist individu ome well integr profil multipl ome genom epigenom transcriptom proteom metabolom antibodyom omic inform expect valuabl health monitor prevent measur precis medicin moreov omic technolog potenti transform medicin tradit symptomori diagnosi treatment diseas toward diseas prevent earli diagnost discuss advanc challeng system biologypow person medicin current stage well prospect view futur person health care end review

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