Article

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data

2023-07-29

Abstract excerpt

<h4>Background</h4> Oncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to a large number of metabolites in a cell and the presence of multiple genes associated with cancer development. <h4>R...

Topics

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

Identifiers and source

Literature Corpus work: 1daf3935-dfd6-54e1-840a-f10c21c98cac
DOI: 10.1101/2023.07.26.550699

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation dataDOI 10.1101/2023.07.26.550699Read

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data.Semantic proximity Read

A new genome-scale model enables prediction of cancer metabolic dependenciesSemantic proximity Read

A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.Semantic proximity Read

Alterations of metabolic genes and metabolites in cancer.Semantic proximity Read

Mining cancer genomes for change-of-metabolic-function mutations.Semantic proximity Read

Charting the cross-functional map between transcription factors and cancer metabolismSemantic proximity Read

Cancer metabolic subtypes and their association with molecular and clinical featuresSemantic proximity Read

A Mechanistic Model for Genome-Scale Estimations of Metabolic ActivitySemantic proximity Read

Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targetsSemantic proximity Read

A-LAVA: Detecting impact of germline variants on metabolic pathways in cancer genomesSemantic proximity Read

Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistanceSemantic proximity Read

Multivariate analysis of metabolic state vulnerabilities across diverse cancer contexts reveals synthetically lethal associationsSemantic proximity Read