Optimally discriminative subnetwork markers predict response to chemotherapy.
about
Integrative approaches for finding modular structure in biological networksIntegrative analysis of cancer imaging readouts by networksPathway-Based Genomics Prediction using Generalized Elastic NetA New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural AlertsFunctional module search in protein networks based on semantic similarity improves the analysis of proteomics data.Data Requirements for Model-Based Cancer Prognosis PredictionOn the performance of de novo pathway enrichment.Network biology methods integrating biological data for translational scienceHigh accordance in prognosis prediction of colorectal cancer across independent datasets by multi-gene module expression profiles.Cancer core modules identification through genomic and transcriptomic changes correlation detection at network level.Identifying stage-specific protein subnetworks for colorectal cancer.Chapter 5: Network biology approach to complex diseases.Classification of time series gene expression in clinical studies via integration of biological networkAssessment of subnetwork detection methods for breast cancerA network module-based method for identifying cancer prognostic signaturesBridging the Gap between Genotype and Phenotype via Network Approaches.Dissecting cancer heterogeneity with a probabilistic genotype-phenotype model.Detection of deregulated modules using deregulatory linked pathDifferential network analysis applied to preoperative breast cancer chemotherapy response.An integer linear programming approach for finding deregulated subgraphs in regulatory networks.Ensemble inference by integrative cancer networks.Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development.Biomarker gene signature discovery integrating network knowledge.Edge biomarkers for classification and prediction of phenotypes.HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology.GTA: a game theoretic approach to identifying cancer subnetwork markers.SPECTRA: An Integrated Knowledge Base for Comparing Tissue and Tumor-Specific PPI Networks in Human.HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screeningsImproved prediction of breast cancer outcome by identifying heterogeneous biomarkers.Including network knowledge into Cox regression models for biomarker signature discovery.Accurate prediction and elucidation of drug resistance based on the robust and reproducible chemoresponse communities.Network module identification-A widespread theoretical bias and best practices.Evaluation of QSAR models for the prediction of ames genotoxicity: a retrospective exercise on the chemical substances registered under the EU REACH regulation.RRHGE: a novel approach to classify the estrogen receptor based breast cancer subtypes.Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix FactorizationEfficacious End User Measures—Part 1: Relative Class Size and End User Problem Domains
P2860
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P2860
Optimally discriminative subnetwork markers predict response to chemotherapy.
description
2011 nî lūn-bûn
@nan
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
2011年论文
@zh
2011年论文
@zh-cn
name
Optimally discriminative subnetwork markers predict response to chemotherapy.
@en
Optimally discriminative subnetwork markers predict response to chemotherapy.
@nl
type
label
Optimally discriminative subnetwork markers predict response to chemotherapy.
@en
Optimally discriminative subnetwork markers predict response to chemotherapy.
@nl
prefLabel
Optimally discriminative subnetwork markers predict response to chemotherapy.
@en
Optimally discriminative subnetwork markers predict response to chemotherapy.
@nl
P2093
P2860
P356
P1433
P1476
Optimally discriminative subnetwork markers predict response to chemotherapy.
@en
P2093
Anna Lapuk
Colin Collins
Kendric Wang
Martin Ester
Phuong Dao
S Cenk Sahinalp
P2860
P304
P356
10.1093/BIOINFORMATICS/BTR245
P407
P577
2011-07-01T00:00:00Z