ArticlePLoS computational biology2014
Systematic evaluation of methods for integration of transcriptomic data into constraint-based models of metabolism.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 218 papers.
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218 citing papers in PubMed, 428 citations in OpenAlex.
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- Predictive Algal Systems Biology: Integrating Omics, Genome-Scale Metabolic Models, and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Review
- Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis.BMC bioinformatics · 2026Article
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- Transcriptome-driven constraint-based modelling reveals metabolic targets for ovarian cancer.Cancer & metabolism · 2026Article
- Predictive multispecies constraint-based metabolic modeling: case studies and best practices.Briefings in bioinformatics · 2026Review
- Flux sampling and context-specific genome-scale metabolic models for biotechnological applications.Trends in biotechnology · 2026Review
- Spatial FBA reveals heterogeneous Warburg niches in renal tumors and lactate consumption in colorectal cancer.NPJ systems biology and applications · 2026Article
- Improved flux profiling in genome-scale modeling of human cell metabolism.Cell reports methods · 2026Article
- Higher order synthetic lethals are keys to minimize cancer treatment effects on non-tumor cells.PloS one · 2026Article
- Evaluating transcriptomic integration for cyanobacterial constraint-based metabolic modelling.Frontiers in bioinformatics · 2026Article
- Modelling reliable metabolic phenotypes by analysing the context-specific transcriptomics data.NPJ systems biology and applications · 2025Article
- Mechanistically informed machine learning links non-canonical TCA cycle activity to Warburg metabolism and hallmarks of malignancy.PLoS computational biology · 2025Article
- Advances in metabolic engineering and fermentation for 3-hydroxypropionic acid biosynthesis: a comprehensive review.World journal of microbiology & biotechnology · 2025Review
- Evaluating plant growth-defense trade-offs by modeling the interaction between primary and secondary metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
158 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Constraint-based models of metabolism are a widely used framework for predicting flux distributions in genome-scale biochemical networks. The number of published methods for integration of transcriptomic data into constraint-based models has been rapidly increasing. So far the predictive capability of these methods has not been critically evaluated and compared. This work presents a survey of recently published methods that use transcript levels to try to improve metabolic flux predictions either by generating flux distributions or by creating context-specific models. A subset of these methods is then systematically evaluated using published data from three different case studies in E. coli and S. cerevisiae. The flux predictions made by different methods using transcriptomic data are compared against experimentally determined extracellular and intracellular fluxes (from 13C-labeling data). The sensitivity of the results to method-specific parameters is also evaluated, as well as their robustness to noise in the data. The results show that none of the methods outperforms the others for all cases. Also, it is observed that for many conditions, the predictions obtained by simple flux balance analysis using growth maximization and parsimony criteria are as good or better than those obtained using methods that incorporate transcriptomic data. We further discuss the differences in the mathematical formulation of the methods, and their relation to the results we have obtained, as well as the connection to the underlying biological principles of metabolic regulation.
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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.