J. Comput. Biol. - A topology-based score for pathway enrichment.

Tópicos

{ gene(2352) biolog(1181) express(1162) }
{ method(1969) cluster(1462) data(1082) }
{ use(976) code(926) identifi(902) }
{ assess(1506) score(1403) qualiti(1306) }
{ framework(1458) process(801) describ(734) }
{ extract(1171) text(1153) clinic(932) }
{ can(774) often(719) complex(702) }
{ take(945) account(800) differ(722) }
{ error(1145) method(1030) estim(1020) }
{ visual(1396) interact(850) tool(830) }
{ data(1714) softwar(1251) tool(1186) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ data(3963) clinic(1234) research(1004) }
{ model(2341) predict(2261) use(1141) }
{ studi(1119) effect(1106) posit(819) }
{ model(2656) set(1616) predict(1553) }
{ group(2977) signific(1463) compar(1072) }
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{ imag(1947) propos(1133) code(1026) }
{ imag(1057) registr(996) error(939) }
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{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ surgeri(1148) surgic(1085) robot(1054) }
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{ system(1050) medic(1026) inform(1018) }
{ model(3480) simul(1196) paramet(876) }
{ activ(1138) subject(705) human(624) }
{ health(1844) social(1437) communiti(874) }
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{ imag(2675) segment(2577) method(1081) }
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{ method(984) reconstruct(947) comput(926) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ risk(3053) factor(974) diseas(938) }
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{ record(1888) medic(1808) patient(1693) }
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{ 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) }
{ cost(1906) reduc(1198) effect(832) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ use(1733) differ(960) four(931) }
{ 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) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Investigators require intuitive tools to rationalize complex datasets generated by transcriptional profiling experiments. Pathway analysis methods, in which differentially expressed genes are mapped to databases of reference pathways to facilitate assessment of relative enrichment, lead investigators more effectively to biologically testable hypotheses. However, once a set of differentially expressed genes is isolated, pathway analysis approaches tend to ignore rich gene expression information and, moreover, do not exploit relationships between transcripts. In this article, we report the development of a new method in which both pathway topology and the magnitude of gene expression changes inform the scoring system, thereby providing a powerful filter in the enrichment of biologically relevant information. When four sample datasets were evaluated with this method, literature mining confirmed that those pathways germane to the physiological process under investigation were highlighted by our method relative to z-score overrepresentation calculations. Moreover, non-relevant processes were downgraded using the method described herein. The inclusion of expression and topological data in the calculation of a pathway regulation score (PRS) facilitated discrimination of key processes in real biological datasets. Specifically, by combining fold-change data for those transcripts exceeding a significance threshold, and by taking into account the potential for altered gene expression to impact upon downstream transcription, one may readily identify those pathways most relevant to pathophysiological processes.

Resumo Limpo

investig requir intuit tool ration complex dataset generat transcript profil experi pathway analysi method differenti express gene map databas refer pathway facilit assess relat enrich lead investig effect biolog testabl hypothes howev set differenti express gene isol pathway analysi approach tend ignor rich gene express inform moreov exploit relationship transcript articl report develop new method pathway topolog magnitud gene express chang inform score system therebi provid power filter enrich biolog relev inform four sampl dataset evalu method literatur mine confirm pathway german physiolog process investig highlight method relat zscore overrepresent calcul moreov nonrelev process downgrad use method describ herein inclus express topolog data calcul pathway regul score prs facilit discrimin key process real biolog dataset specif combin foldchang data transcript exceed signific threshold take account potenti alter gene express impact upon downstream transcript one may readili identifi pathway relev pathophysiolog process

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