ArticleMetabolites2019
Genome-Scale Metabolic Modeling with Protein Expressions of Normal and Cancerous Colorectal Tissues for Oncogene Inference.
Article in Metabolites, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 21 citations in OpenAlex.
- Identification of Anticancer Enzymes and Biomarkers for Hepatocellular Carcinoma through Constraint-Based Modeling.Molecules (Basel, Switzerland) · 2024Article
- Cell-specific genome-scale metabolic modeling of SARS-CoV-2-infected lung to identify antiviral enzymes.FEBS open bio · 2023Article
- Identifying essential genes in genome-scale metabolic models of consensus molecular subtypes of colorectal cancer.PloS one · 2023Article
- Fuzzy optimization for identifying anti-cancer targets with few side effects in constraint-based models of head and neck cancer.Royal Society open science · 2022Article
- Human/SARS-CoV-2 genome-scale metabolic modeling to discover potential antiviral targets for COVID-19.Journal of the Taiwan Institute of Chemical Engineers · 2022Article
- Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.Frontiers in oncology · 2022Review
- Computer-Aided Design for Identifying Anticancer Targets in Genome-Scale Metabolic Models of Colon Cancer.Biology · 2021Article
- Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment.Cancers · 2021Review
- Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Although cancer has historically been regarded as a cell proliferation disorder, it has recently been considered a metabolic disease. The first discovery of metabolic alterations in cancer cells refers to Otto Warburg's observations. Cancer metabolism results in alterations in metabolic fluxes that are evident in cancer cells compared with most normal tissue cells. This study applied protein expressions of normal and cancer cells to reconstruct two tissue-specific genome-scale metabolic models. Both models were employed in a tri-level optimization framework to infer oncogenes. Moreover, this study also introduced enzyme pseudo-coding numbers in the gene association expression to avoid performing posterior decision-making that is necessary for the reaction-based method. Colorectal cancer (CRC) was the topic of this case study, and 20 top-ranked oncogenes were determined. Notably, these dysregulated genes were involved in various metabolic subsystems and compartments. We found that the average similarity ratio for each dysregulation is higher than 98%, and the extent of similarity for flux changes is higher than 93%. On the basis of surveys of PubMed and GeneCards, these oncogenes were also investigated in various carcinomas and diseases. Most dysregulated genes connect to
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.