J. Comput. Biol. - Node fingerprinting: an efficient heuristic for aligning biological networks.

Tópicos

{ sequenc(1873) structur(1644) protein(1328) }
{ gene(2352) biolog(1181) express(1162) }
{ algorithm(1844) comput(1787) effici(935) }
{ network(2748) neural(1063) input(814) }
{ research(1218) medic(880) student(794) }
{ method(2212) result(1239) propos(1039) }
{ can(774) often(719) complex(702) }
{ data(1737) use(1416) pattern(1282) }
{ patient(2315) diseas(1263) diabet(1191) }
{ method(1557) propos(1049) approach(1037) }
{ control(1307) perform(991) simul(935) }
{ general(901) number(790) one(736) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }
{ inform(2794) health(2639) internet(1427) }
{ method(1219) similar(1157) match(930) }
{ treatment(1704) effect(941) patient(846) }
{ data(2317) use(1299) case(1017) }
{ activ(1138) subject(705) human(624) }
{ take(945) account(800) differ(722) }
{ error(1145) method(1030) estim(1020) }
{ model(2220) cell(1177) simul(1124) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ can(981) present(881) function(850) }
{ high(1669) rate(1365) level(1280) }
{ drug(1928) target(777) effect(648) }
{ activ(1452) weight(1219) physic(1104) }
{ 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) }
{ featur(3375) classif(2383) classifi(1994) }
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{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ 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) }
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{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ care(1570) inform(1187) nurs(1089) }
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{ featur(1941) imag(1645) propos(1176) }
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{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
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{ system(1050) medic(1026) inform(1018) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ 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) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ 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) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ 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) }
{ process(1125) use(805) approach(778) }

Resumo

With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.

Resumo Limpo

continu increas avail biolog data improv biolog model biolog network analysi becom promis area research emerg techniqu analysi biolog network network align network align use calcul genet distanc similar regulatori structur effect extern forc gene express depict condit activ express modul cancer network align algorithm complex therefor must reli heurist ideal effici accur possibl major current techniqu network align reli precomput inform protein sequenc align tunabl network align paramet may introduc increas comput overhead present algorithm call node fingerprint nf appropri perform global pairwis network align without precomput tune can fulli parallel abl quick comput accur align two biolog network perform well better exist algorithm biolog simul data fewer comput resourc algorithm valid perform demonstr low comput resourc requir nf

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