Genome-scale analysis of interaction dynamics reveals organization of biological networks.
about
Dynamic control of selectivity in the ubiquitination pathway revealed by an ASP to GLU substitution in an intra-molecular salt-bridge networkIdentification of highly synchronized subnetworks from gene expression data.Predicting cancer prognosis using functional genomics data sets.DTW-MIC Coexpression Networks from Time-Course Data.HINT: High-quality protein interactomes and their applications in understanding human disease.Minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers.Detecting temporal protein complexes from dynamic protein-protein interaction networks.Simple topological features reflect dynamics and modularity in protein interaction networks.ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancersIntegrated web visualizations for protein-protein interaction databasesRevealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential NetworksA New Algorithm to Optimize Maximal Information CoefficientBiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes.Cross-species protein interactome mapping reveals species-specific wiring of stress response pathways.Spatial Colocalization of Human Ohnolog Pairs Acts to Maintain Dosage-BalanceProtein complex detection based on partially shared multi-view clusteringRapidMic: Rapid Computation of the Maximal Information Coefficient.Schizophrenia at a genetics crossroads: where to now?Integrated network analysis reveals distinct regulatory roles of transcription factors and microRNAsEvaluating predictive performance of network biomarkers with network structures.Links between critical proteins drive the controllability of protein interaction networks.Most associations between transcript features and gene expression are monotonic.
P2860
Q28484775-DCAAECD8-B356-49A9-8389-3E45023532F7Q30658327-BC7F198A-75EF-4197-83E3-6069D01F1654Q30869262-FAF7411D-1EFF-406C-996F-37CA0BBAF5F9Q31065775-63C47985-C599-41AC-8CD3-B838E18334D5Q34356822-985E6FAB-62CE-4227-AB4F-CDD244BED0DBQ34513638-B1743E59-8B15-4BEE-9DD9-4FD74245D554Q34887961-5A8C6F33-66C3-4833-8820-CF6F31A2D42BQ35018008-AE5030D5-92FE-4BF3-A43F-960E3C42D548Q35359098-7C68BC46-9BAA-40B5-BAB9-0DBE31F2B26DQ35664625-A45E12DD-D40C-46E2-ADA4-F404006240A5Q35666295-29F01F80-7289-4A8A-895B-6B1CD63DC76BQ36059006-168683C6-4357-4732-8F3D-67E5D40936EDQ36086958-A987FFA6-A512-47F4-A49E-1F7E22EA567DQ37184407-422868BE-BA37-40DA-BE1A-A9E0BB6CF9BFQ37184701-F380AE6C-5097-4563-8C12-F9D05D949D24Q37254749-99A0D92A-CDC4-44C1-B21A-D1A4278016DFQ37577865-433A7328-8CE6-4CC7-B651-F661F332BCE3Q39880626-EC58AB22-B7E8-4A69-B589-E668D7C8436BQ42704831-51BA84CF-E6A3-4605-942C-D619DB5D16FAQ43423033-B9C36AC7-04D8-48C4-B6C3-53DAB4231780Q48292362-94879FEA-5216-440F-BC32-B38559D1AA86Q53588530-FFEF9606-12F9-4EED-AADD-A7537966D713
P2860
Genome-scale analysis of interaction dynamics reveals organization of biological networks.
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
@zh
2012年學術文章
@zh-hant
name
Genome-scale analysis of inter ...... zation of biological networks.
@ast
Genome-scale analysis of inter ...... zation of biological networks.
@en
type
label
Genome-scale analysis of inter ...... zation of biological networks.
@ast
Genome-scale analysis of inter ...... zation of biological networks.
@en
prefLabel
Genome-scale analysis of inter ...... zation of biological networks.
@ast
Genome-scale analysis of inter ...... zation of biological networks.
@en
P2093
P2860
P356
P1433
P1476
Genome-scale analysis of inter ...... zation of biological networks.
@en
P2093
Haiyuan Yu
Jaaved Mohammed
Jishnu Das
P2860
P304
P356
10.1093/BIOINFORMATICS/BTS283
P407
P577
2012-05-09T00:00:00Z