Comput Math Methods Med - Genomic biomarkers for personalized medicine: development and validation in clinical studies.

Tópicos

{ gene(2352) biolog(1181) express(1162) }
{ cancer(2502) breast(956) screen(824) }
{ research(1085) discuss(1038) issu(1018) }
{ studi(2440) review(1878) systemat(933) }
{ cost(1906) reduc(1198) effect(832) }
{ implement(1333) system(1263) develop(1122) }
{ system(1976) rule(880) can(841) }
{ compound(1573) activ(1297) structur(1058) }
{ patient(1821) servic(1111) care(1106) }
{ can(774) often(719) complex(702) }
{ measur(2081) correl(1212) valu(896) }
{ take(945) account(800) differ(722) }
{ treatment(1704) effect(941) patient(846) }
{ framework(1458) process(801) describ(734) }
{ algorithm(1844) comput(1787) effici(935) }
{ data(1714) softwar(1251) tool(1186) }
{ general(901) number(790) one(736) }
{ case(1353) use(1143) diagnosi(1136) }
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{ spatial(1525) area(1432) region(1030) }
{ model(2656) set(1616) predict(1553) }
{ data(3008) multipl(1320) sourc(1022) }
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{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
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{ featur(3375) classif(2383) classifi(1994) }
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{ assess(1506) score(1403) qualiti(1306) }
{ 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) }
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{ clinic(1479) use(1117) guidelin(835) }
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{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ 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) }
{ 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) }
{ data(2317) use(1299) case(1017) }
{ 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) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ use(976) code(926) identifi(902) }
{ 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) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The establishment of high-throughput technologies has brought substantial advances to our understanding of the biology of many diseases at the molecular level and increasing expectations on the development of innovative molecularly targeted treatments and molecular biomarkers or diagnostic tests in the context of clinical studies. In this review article, we position the two critical statistical analyses of high-dimensional genomic data, gene screening and prediction, in the framework of development and validation of genomic biomarkers or signatures, through taking into consideration the possible different strategies for developing genomic signatures. A wide variety of biomarker-based clinical trial designs to assess clinical utility of a biomarker or a new treatment with a companion biomarker are also discussed.

Resumo Limpo

establish highthroughput technolog brought substanti advanc understand biolog mani diseas molecular level increas expect develop innov molecular target treatment molecular biomark diagnost test context clinic studi review articl posit two critic statist analys highdimension genom data gene screen predict framework develop valid genom biomark signatur take consider possibl differ strategi develop genom signatur wide varieti biomarkerbas clinic trial design assess clinic util biomark new treatment companion biomark also discuss

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