J Integr Bioinform - Web2.0 paves new ways for collaborative and exploratory analysis of chemical compounds in spectrometry data.

Tópicos

{ research(1218) medic(880) student(794) }
{ data(1714) softwar(1251) tool(1186) }
{ health(1844) social(1437) communiti(874) }
{ data(2317) use(1299) case(1017) }
{ method(984) reconstruct(947) comput(926) }
{ can(774) often(719) complex(702) }
{ research(1085) discuss(1038) issu(1018) }
{ monitor(1329) mobil(1314) devic(1160) }
{ result(1111) use(1088) new(759) }
{ import(1318) role(1303) understand(862) }
{ clinic(1479) use(1117) guidelin(835) }
{ visual(1396) interact(850) tool(830) }
{ system(1976) rule(880) can(841) }
{ method(1219) similar(1157) match(930) }
{ chang(1828) time(1643) increas(1301) }
{ method(1557) propos(1049) approach(1037) }
{ design(1359) user(1324) use(1319) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ system(1050) medic(1026) inform(1018) }
{ studi(1119) effect(1106) posit(819) }
{ model(3480) simul(1196) paramet(876) }
{ data(3008) multipl(1320) sourc(1022) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ search(2224) databas(1162) retriev(909) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ model(2341) predict(2261) use(1141) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ 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) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ 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) }
{ 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) }
{ 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) }
{ 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

In nowadays life science projects, sharing data and data interpretation is becoming increasingly important. This considerably calls for novel information technology approaches, which enable the integration of expert knowledge from different disciplines in combination with advanced data analysis facilities in a collaborative manner. Since the recent development of web technologies offers scientific communities new ways for cooperation and communication, we propose a fully web-based software approach for the collaborative analysis of bioimage data and demonstrate the applicability of Web2.0 techniques to ion mobility spectrometry image data. Our approach allows collaborating experts to easily share, explore and discuss complex image data without any installation of software packages. Scientists only need a username and a password to get access to our system and can directly start exploring and analyzing their data.

Resumo Limpo

nowaday life scienc project share data data interpret becom increas import consider call novel inform technolog approach enabl integr expert knowledg differ disciplin combin advanc data analysi facil collabor manner sinc recent develop web technolog offer scientif communiti new way cooper communic propos fulli webbas softwar approach collabor analysi bioimag data demonstr applic web techniqu ion mobil spectrometri imag data approach allow collabor expert easili share explor discuss complex imag data without instal softwar packag scientist need usernam password get access system can direct start explor analyz data

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