A comparison of the functional modules identified from time course and static PPI network data.
about
Construction and application of dynamic protein interaction network based on time course gene expression data.Identification of highly synchronized subnetworks from gene expression data.Identifying dynamic protein complexes based on gene expression profiles and PPI networks.DyCoNet: a Gephi plugin for community detection in dynamic complex networks.Towards the identification of protein complexes and functional modules by integrating PPI network and gene expression dataMetabolic flux-based modularity using shortest retroactive distances.Identifying essential proteins from active PPI networks constructed with dynamic gene expressionTranscription factor networks in Drosophila melanogaster.Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer's disease like pathology.Detecting conserved protein complexes using a dividing-and-matching algorithm and unequally lenient criteria for network comparisonA two-layer integration framework for protein complex detection.Mining Temporal Protein Complex Based on the Dynamic PIN Weighted with Connected Affinity and Gene Co-ExpressionNetwork analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.BiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes.Predicting essential proteins based on subcellular localization, orthology and PPI networks.Functional Module Analysis for Gene Coexpression Networks with Network Integration.Identification of protein complexes from multi-relationship protein interaction networksDynamic protein-protein interaction subnetworks of lung cancer in cases with smoking history.Detecting protein complexes from active protein interaction networks constructed with dynamic gene expression profiles.Constructing Networks of Organelle Functional Modules in Arabidopsis.Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes.msiDBN: a method of identifying critical proteins in dynamic PPI networks.Computational approaches to predicting essential proteins: a survey.Dynamic protein interaction network construction and applications.Protein-protein interactions: detection, reliability assessment and applications.Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.DyNetViewer: a Cytoscape app for dynamic network construction, analysis and visualization.The fundamental advantages of temporal networks.CPredictor3.0: detecting protein complexes from PPI networks with expression data and functional annotations.Mapping biological process relationships and disease perturbations within a pathway network.Detecting complexes from edge-weighted PPI networks via genes expression analysis.
P2860
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P2860
A comparison of the functional modules identified from time course and static PPI network data.
description
2011 nî lūn-bûn
@nan
2011 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
A comparison of the functional ...... e and static PPI network data.
@ast
A comparison of the functional ...... e and static PPI network data.
@en
type
label
A comparison of the functional ...... e and static PPI network data.
@ast
A comparison of the functional ...... e and static PPI network data.
@en
prefLabel
A comparison of the functional ...... e and static PPI network data.
@ast
A comparison of the functional ...... e and static PPI network data.
@en
P2093
P2860
P356
P1433
P1476
A comparison of the functional ...... e and static PPI network data.
@en
P2093
P2860
P2888
P356
10.1186/1471-2105-12-339
P577
2011-08-15T00:00:00Z
P5875
P6179
1000401501