Discovering molecular pathways from protein interaction and gene expression data.
about
Biomedical discovery acceleration, with applications to craniofacial developmentIdentification of functional modules using network topology and high-throughput data.Cluster analysis of networks generated through homology: automatic identification of important protein communities involved in cancer metastasisNetwork-based prediction of protein functionThe effects of normalization on the correlation structure of microarray dataAutomation of gene assignments to metabolic pathways using high-throughput expression data.Integrative approaches for finding modular structure in biological networksDEGAS: de novo discovery of dysregulated pathways in human diseasesIntegrated analysis of transcriptomic and proteomic dataCurrent approaches to gene regulatory network modellingNeuroinformatic analyses of common and distinct genetic components associated with major neuropsychiatric disordersChapter 2: Data-driven view of disease biologyENNET: inferring large gene regulatory networks from expression data using gradient boostingIdentification of mutated core cancer modules by integrating somatic mutation, copy number variation, and gene expression data.Gene network inference by fusing data from diverse distributionsCGI: a new approach for prioritizing genes by combining gene expression and protein-protein interaction data.A Markov random field model for network-based analysis of genomic data.Identifying protein complexes directly from high-throughput TAP data with Markov random fields.Using local gene expression similarities to discover regulatory binding site modules.A Bayesian network driven approach to model the transcriptional response to nitric oxide in Saccharomyces cerevisiae.Gene expression trees in lymphoid developmentInferring biological functions and associated transcriptional regulators using gene set expression coherence analysisAn in silico method for detecting overlapping functional modules from composite biological networksInferring pathway activity toward precise disease classificationMaximization of negative correlations in time-course gene expression data for enhancing understanding of molecular pathwaysGATE: software for the analysis and visualization of high-dimensional time series expression data.Searching for functional gene modules with interaction component modelsEvaluating between-pathway models with expression dataSimultaneous clustering of multiple gene expression and physical interaction datasets.A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network.Determining modular organization of protein interaction networks by maximizing modularity densityIdentifying dysfunctional crosstalk of pathways in various regions of Alzheimer's disease brainsModule discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.Recent advances in clustering methods for protein interaction networksCASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method.Disease gene interaction pathways: a potential framework for how disease genes associate by disease-risk modules.Prediction and functional analysis of the sweet orange protein-protein interaction networkBayesian hierarchical models for protein networks in single-cell mass cytometry.Physical protein-protein interactions predicted from microarraysTREEGL: reverse engineering tree-evolving gene networks underlying developing biological lineages.
P2860
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P2860
Discovering molecular pathways from protein interaction and gene expression data.
description
2003 nî lūn-bûn
@nan
2003 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2003 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2003年の論文
@ja
2003年論文
@yue
2003年論文
@zh-hant
2003年論文
@zh-hk
2003年論文
@zh-mo
2003年論文
@zh-tw
2003年论文
@wuu
name
Discovering molecular pathways from protein interaction and gene expression data.
@ast
Discovering molecular pathways from protein interaction and gene expression data.
@en
type
label
Discovering molecular pathways from protein interaction and gene expression data.
@ast
Discovering molecular pathways from protein interaction and gene expression data.
@en
prefLabel
Discovering molecular pathways from protein interaction and gene expression data.
@ast
Discovering molecular pathways from protein interaction and gene expression data.
@en
P2093
P356
P1433
P1476
Discovering molecular pathways from protein interaction and gene expression data.
@en
P2093
P304
P356
10.1093/BIOINFORMATICS/BTG1037
P407
P478
19 Suppl 1
P577
2003-01-01T00:00:00Z