about
Unequal evolutionary conservation of human protein interactions in interologous networksUnraveling protein networks with power graph analysisComprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiaeThe yeast kinome displays scale free topology with functional hub clustersMethods for biological data integration: perspectives and challengesMining protein interactomes to improve their reliability and support the advancement of network medicineProbing the extent of randomness in protein interaction networksDominating biological networksNetwork topology reveals key cardiovascular disease genesGraphlet characteristics in directed networksExploring the structure and function of temporal networks with dynamic graphletsKnowledge Discovery and interactive Data Mining in Bioinformatics--State-of-the-Art, future challenges and research directionsGlobal geometric affinity for revealing high fidelity protein interaction networkSystems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics dataGeometric de-noising of protein-protein interaction networksDomain-mediated protein interaction prediction: From genome to network.GR-Align: fast and flexible alignment of protein 3D structures using graphlet degree similarity.Revealing the hidden language of complex networks.Optimized null model for protein structure networks.M-BISON: microarray-based integration of data sources using networks.The post-genomic era of biological network alignmentIdentification of putative drug targets for human sperm-egg interaction defect using protein network approach.Systems biology in the context of big data and networks.Graph-based inter-subject pattern analysis of FMRI data.Integration of molecular network data reconstructs Gene OntologySome protein interaction data do not exhibit power law statistics.MAVisto: a tool for the exploration of network motifs.Decomposition of overlapping protein complexes: a graph theoretical method for analyzing static and dynamic protein associations.Inferring topology from clustering coefficients in protein-protein interaction networks.Not all scale-free networks are born equal: the role of the seed graph in PPI network evolution.GraphCrunch: a tool for large network analyses.Evidence of probabilistic behaviour in protein interaction networksDeducing topology of protein-protein interaction networks from experimentally measured sub-networks.Fine-scale dissection of functional protein network organization by statistical network analysis.Incomplete and noisy network data as a percolation process.Modular Organization of Residue-Level Contacts Shapes the Selection Pressure on Individual Amino Acid Sites of Ribosomal Proteins.Unified Alignment of Protein-Protein Interaction Networks.Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data.Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection.A curve shaped description of large networks, with an application to the evaluation of network models.
P2860
Q21092867-48F653CD-3325-4798-B254-6D7EBF03C3CCQ21145374-ABD54AFB-7517-46C4-B813-6CDD186A2ABEQ24675519-EAE17050-E2EF-40D5-8B13-08301480AA72Q24816173-8C137948-09DB-4340-B667-9B64579131F4Q26778582-C1510FFA-D86C-4771-95AC-DD2B58EAE481Q26781142-5AFE353A-099D-40E5-AE90-257314F378D3Q27337213-BA07146D-A472-4B7B-84CD-75C8B250A30CQ28476723-8B44B359-5A2E-45C8-8885-2CADD21BCA65Q28535390-FA1E98F2-99D8-4C7D-9DB5-866B0E825C0EQ28595997-E470CAF6-E3C0-4537-A9BF-4FDC8ECDDC40Q28603784-3CD5C166-3F60-4E09-9091-963EAC495761Q28654387-F6CFCB3B-6EA2-47C1-8BDA-9B73289A938CQ28740501-4E9D1D53-B599-4774-9587-5257EFBFEACAQ28748376-150750D9-1655-49BD-8316-4DBE2ED49967Q28752231-0949D7AE-9344-43C7-B33A-CB52761E5AF1Q30010117-09A2ACBF-3E20-4A34-9597-27009448DACAQ30358085-F8FE1283-C8A5-4FF1-9B32-975F33347244Q30360831-AD5811D6-F0AA-489A-8517-DD28D363A266Q30378442-B7397D44-B501-4A14-B579-2EB79B9B2159Q30482057-AF2EE6B5-3356-4365-9741-C5E77352F3DAQ30490889-0A92972B-46BF-4FE6-BF27-78F0D883617AQ30658102-4E8E3ED1-3BF6-4DFC-AF5B-B2E7240DFB69Q30834336-39045017-B17E-4818-840D-2D24CF32DDFEQ30843022-186E711D-F401-4D07-ACFC-AE36A7EA57EEQ30845305-22326E66-1D68-4FDF-932F-5236996B4643Q30862468-3BD98616-8440-434D-807C-6BD15D47C441Q33219560-EB304632-C7D8-48B5-9D5A-E43D38B3222BQ33244521-8E7793D6-C868-4972-A641-3638867B0ACCQ33265102-95B3757A-7916-4715-86E2-C25E79BF3D1CQ33290222-F1C04432-C9DB-4C10-B1D4-F108ECAD858BQ33317101-0F31A7F6-4A1A-4240-9F13-83B289219B43Q33317634-DFD225BF-DFBB-45F0-B3AD-399ADD55940FQ33348854-E1944C9F-F562-45DE-B71F-7E902CC582B6Q33474347-B5715567-03CF-4B61-A876-D71B66B2C935Q33551129-3289B845-BA2C-487E-A287-65FAC839029BQ33553759-79D0A562-9349-4127-9F8F-D2E599415D7BQ33681051-C5253EA0-82D9-4661-82E5-8D026E438747Q33684509-7406ED20-C8AD-4C0E-93FD-07836C93BE09Q33704536-CE30F8D8-E04A-40A4-8999-8343B71F180FQ33911336-263F3FB8-5ED1-44A3-A567-46EB7C9940C4
P2860
description
2004 nî lūn-bûn
@nan
2004年の論文
@ja
2004年学术文章
@wuu
2004年学术文章
@zh
2004年学术文章
@zh-cn
2004年学术文章
@zh-hans
2004年学术文章
@zh-my
2004年学术文章
@zh-sg
2004年學術文章
@yue
2004年學術文章
@zh-hant
name
Modeling interactome: scale-free or geometric?
@en
Modeling interactome: scale-free or geometric?
@nl
type
label
Modeling interactome: scale-free or geometric?
@en
Modeling interactome: scale-free or geometric?
@nl
prefLabel
Modeling interactome: scale-free or geometric?
@en
Modeling interactome: scale-free or geometric?
@nl
P356
P1433
P1476
Modeling interactome: scale-free or geometric?
@en
P2093
D G Corneil
I Jurisica
P304
P356
10.1093/BIOINFORMATICS/BTH436
P407
P577
2004-07-29T00:00:00Z
P5875
P698
P818
q-bio/0404017