Brief. Bioinformatics - Toward the dynamic interactome: it's about time.

Tópicos

{ gene(2352) biolog(1181) express(1162) }
{ network(2748) neural(1063) input(814) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ bind(1733) structur(1185) ligand(1036) }
{ howev(809) still(633) remain(590) }
{ model(3480) simul(1196) paramet(876) }
{ patient(2315) diseas(1263) diabet(1191) }
{ cost(1906) reduc(1198) effect(832) }
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{ 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) }
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{ high(1669) rate(1365) level(1280) }
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{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Dynamic molecular interactions play a central role in regulating the functioning of cells and organisms. The availability of experimentally determined large-scale cellular networks, along with other high-throughput experimental data sets that provide snapshots of biological systems at different times and conditions, is increasingly helpful in elucidating interaction dynamics. Here we review the beginnings of a new subfield within computational biology, one focused on the global inference and analysis of the dynamic interactome. This burgeoning research area, which entails a shift from static to dynamic network analysis, promises to be a major step forward in our ability to model and reason about cellular function and behavior.

Resumo Limpo

dynam molecular interact play central role regul function cell organ avail experiment determin largescal cellular network along highthroughput experiment data set provid snapshot biolog system differ time condit increas help elucid interact dynam review begin new subfield within comput biolog one focus global infer analysi dynam interactom burgeon research area entail shift static dynam network analysi promis major step forward abil model reason cellular function behavior

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