ArticleCell systems2017
A Systematic Evaluation of Methods for Tailoring Genome-Scale Metabolic Models.
Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
125 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-scale metabolic modeling reveals increased reliance on valine catabolism in clinical isolates of Klebsiella pneumoniae.NPJ systems biology and applications · 2022Pooled it
- Unraveling Aberrant Metabolic Patterns in Alzheimer's Disease Subtypes: From Perturbed Metabolic Pathways to Candidate Drug Targets.Molecular neurobiology · 2026Article
- A community reconstruction of Chinese hamster metabolism and structural systems biology elucidate metabolic rewiring in lactate-free CHO cells.Cell systems · 2026Article
- Integrating Genome-Scale Metabolic Modeling with Machine Learning Improves Gene Essentiality Prediction in Triple-Negative Breast Cancer.International journal of molecular sciences · 2026Article
- XomicsToModel: omics data integration and generation of thermodynamically consistent metabolic models.Nature protocols · 2026Article
- Predictive Algal Systems Biology: Integrating Omics, Genome-Scale Metabolic Models, and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Review
- Spatial FBA reveals heterogeneous Warburg niches in renal tumors and lactate consumption in colorectal cancer.NPJ systems biology and applications · 2026Article
- Modeling tissue-specific Drosophila metabolism identifies high sugar diet-induced metabolic dysregulation in muscle at reaction and pathway levels.Nature communications · 2026Article
- Higher order synthetic lethals are keys to minimize cancer treatment effects on non-tumor cells.PloS one · 2026Article
- Modelling reliable metabolic phenotypes by analysing the context-specific transcriptomics data.NPJ systems biology and applications · 2025Article
- Beyond Bulk Metabolomics: Emerging Technologies for Defining Cell-Type Specific Metabolic Pathways in Health and Disease.Biomolecules · 2025Review
- Constraint based modeling of drug induced metabolic changes in a cancer cell line.NPJ systems biology and applications · 2025Article
- Optimization-based framework with flux balance analysis (FBA) and metabolic pathway analysis (MPA) for identifying metabolic objective functions.PLoS computational biology · 2025Article
- ThermOptCobra: Thermodynamically optimal construction and analysis of metabolic networks for reliable phenotype predictions.iScience · 2025Article
- Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Modeling the metabolic response of A2780 ovarian cancer cells to gold-based cytotoxic drugs.NPJ systems biology and applications · 2025Article
- MACAW: a method for semi-automatic detection of errors in genome-scale metabolic models.Genome biology · 2025Article
- UnifiedGreatMod: a new holistic modelling paradigm for studying biological systems on a complete and harmonious scale.Bioinformatics (Oxford, England) · 2025Article
- Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025Review
- Integration of metatranscriptomics data improves the predictive capacity of microbial community metabolic models.The ISME journal · 2025Article
65 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Genome-scale models of metabolism can illuminate the molecular basis of cell phenotypes. Since some enzymes are only active in specific cell types, several algorithms use omics data to construct cell-line- and tissue-specific metabolic models from genome-scale models. However, these methods are often not rigorously benchmarked, and it is unclear how algorithm and parameter selection (e.g., gene expression thresholds, metabolic constraints) affects model content and predictive accuracy. To investigate this, we built hundreds of models of four different cancer cell lines using six algorithms, four gene expression thresholds, and three sets of metabolic constraints. Model content varied substantially across different parameter sets, but the algorithms generally increased accuracy in gene essentiality predictions. However, model extraction method choice had the largest impact on model accuracy. We further highlight how assumptions during model development influence model prediction accuracy. These insights will guide further development of context-specific models, thus more accurately resolving genotype-phenotype relationships.
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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.