Article

PRER: A Patient Representation with Pairwise Relative Expression of Proteins on Biological Networks

2020-06-16

Abstract excerpt

Changes in protein and gene expression levels are often used as features to predictive models such as survival prediction. A common strategy to aggregate information on individual proteins is to integrate the expression information with biological networks. We propose a novel patient representation in this work where we integrate proteins’ expression levels with the protein-protein interaction (PPI) networks. Pati...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6b4d1c3b-9e03-5b8e-9dfd-4e9375daf3eb
DOI: 10.1101/2020.06.16.153999

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

PRER: A Patient Representation with Pairwise Relative Expression of Proteins on Biological NetworksDOI 10.1101/2020.06.16.153999Read

ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancersSemantic proximity Read

Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction.Semantic proximity Read

Construct a molecular associations network to systematically understand intermolecular associations in <i>Human</i> cellsSemantic proximity Read

netDx: Interpretable patient classification using integrated patient similarity networksSemantic proximity Read

Learning Patient Similarity from Genomics for Precision OncologySemantic proximity Read

DiCE: differential centrality-ensemble analysis based on gene expression profiles and protein-protein interaction networkSemantic proximity Read

netDx: Software for building interpretable patient classifiers by multi-'omic data integration using patient similarity networksSemantic proximity Read

PAN: Personalized Annotation-based Networks for the Prediction of Breast Cancer RelapseSemantic proximity Read

Mutual interactors as a principle for phenotype discovery in molecular interaction networks.Semantic proximity Read

PINT: Pathway-pathway interactions for predicting interpretable clinical outcomes from gene expressionSemantic proximity Read

Sequence Representations and Their Utility for Predicting Protein-protein InteractionsSemantic proximity Read

Topologically inferring risk-active pathways toward precise cancer classification by directed random walkSemantic proximity Read