Brief. Bioinformatics - High-performance analysis of biological systems dynamics with the DiVinE model checker.

Tópicos

{ gene(2352) biolog(1181) express(1162) }
{ data(1737) use(1416) pattern(1282) }
{ method(2212) result(1239) propos(1039) }
{ framework(1458) process(801) describ(734) }
{ howev(809) still(633) remain(590) }
{ data(1714) softwar(1251) tool(1186) }
{ model(3480) simul(1196) paramet(876) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ import(1318) role(1303) understand(862) }
{ record(1888) medic(1808) patient(1693) }
{ use(2086) technolog(871) perceiv(783) }
{ result(1111) use(1088) new(759) }
{ can(774) often(719) complex(702) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ problem(2511) optim(1539) algorithm(950) }
{ method(1557) propos(1049) approach(1037) }
{ featur(1941) imag(1645) propos(1176) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ sampl(1606) size(1419) use(1276) }
{ can(981) present(881) function(850) }
{ use(976) code(926) identifi(902) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ 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) }
{ patient(2315) diseas(1263) diabet(1191) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ 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) }
{ extract(1171) text(1153) clinic(932) }
{ 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) }
{ 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) }
{ model(2341) predict(2261) use(1141) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ health(3367) inform(1360) care(1135) }
{ 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) }
{ model(2656) set(1616) predict(1553) }
{ 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) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The current interest in systems biology is to gain a better understanding of how the complex dynamic behaviour of the cell emerges from mutual interactions of molecular species. When solving such a nontrivial goal, biological data have to be necessarily integrated with mathematical modelling and computer analysis. Since the key aspect of biological modelling is based on unifying several kinds of data captured in terms of large-scale biological networks, scalable and automatized methods are necessary to obtain novel predictions and understanding. In this review, we provide a brief description of the tool DiVinE adapted for automatized analysis of biological systems dynamics. The tool employs high-performance computing techniques to enable analysis of large models.

Resumo Limpo

current interest system biolog gain better understand complex dynam behaviour cell emerg mutual interact molecular speci solv nontrivi goal biolog data necessarili integr mathemat model comput analysi sinc key aspect biolog model base unifi sever kind data captur term largescal biolog network scalabl automat method necessari obtain novel predict understand review provid brief descript tool divin adapt automat analysi biolog system dynam tool employ highperform comput techniqu enabl analysi larg model

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