ArticlePLoS computational biology2019
Increasing consensus of context-specific metabolic models by integrating data-inferred cell functions.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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Who cites it
44 citing papers in PubMed.
- Metabolic Task Analysis Reveals Distinct Metabotypes in End-Stage Dilated Cardiomyopathy.Circulation. Genomic and precision medicine · 2026Article
- A community reconstruction of Chinese hamster metabolism and structural systems biology elucidate metabolic rewiring in lactate-free CHO cells.Cell systems · 2026Article
- Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis.BMC bioinformatics · 2026Article
- Systematic data-driven genome-scale metabolic model reduction for bioprocess modeling: CHO culture case study.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
- Modelling reliable metabolic phenotypes by analysing the context-specific transcriptomics data.NPJ systems biology and applications · 2025Article
- Constraint based modeling of drug induced metabolic changes in a cancer cell line.NPJ systems biology and applications · 2025Article
- Immunometabolism at the crossroads of infection: mechanistic and systems-level perspectives from host and pathogen.Immunometabolism (Cobham, Surrey) · 2025Review
- Metatranscriptomics-based metabolic modeling of patient-specific urinary microbiome during infection.NPJ biofilms and microbiomes · 2025Article
- Temporal analysis of doxorubicin-induced cardiac toxicity and hypertrophy.NPJ systems biology and applications · 2025Article
- Metabolic modeling elucidates phenformin and atpenin A5 as broad-spectrum antiviral drugs against RNA viruses.Communications biology · 2025Article
- Atlas-scale metabolic activities inferred from single-cell and spatial transcriptomics.bioRxiv : the preprint server for biology · 2025Article
- Article
- Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025Review
- Adding metabolic tasks to human GEM models to improve the study of gene targets and their associated toxicities.Scientific reports · 2024Article
- Inferring secretory and metabolic pathway activity from omic data with secCellFie.Metabolic engineering · 2024Article
- Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations.Briefings in bioinformatics · 2023Review
- How reliable are Chinese hamster ovary (CHO) cell genome-scale metabolic models?Biotechnology and bioengineering · 2023Article
- Extracting functionally accurate context-specific models of Atlantic salmon metabolism.NPJ systems biology and applications · 2023Article
- Context-Specific Genome-Scale Metabolic Modelling and Its Application to the Analysis of COVID-19 Metabolic Signatures.Metabolites · 2023Review
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4 authors.
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Abstract
Genome-scale metabolic models provide a valuable context for analyzing data from diverse high-throughput experimental techniques. Models can quantify the activities of diverse pathways and cellular functions. Since some metabolic reactions are only catalyzed in specific environments, several algorithms exist that build context-specific models. However, these methods make differing assumptions that influence the content and associated predictive capacity of resulting models, such that model content varies more due to methods used than cell types. Here we overcome this problem with a novel framework for inferring the metabolic functions of a cell before model construction. For this, we curated a list of metabolic tasks and developed a framework to infer the activity of these functionalities from transcriptomic data. We protected the data-inferred tasks during the implementation of diverse context-specific model extraction algorithms for 44 cancer cell lines. We show that the protection of data-inferred metabolic tasks decreases the variability of models across extraction methods. Furthermore, resulting models better capture the actual biological variability across cell lines. This study highlights the potential of using biological knowledge, inferred from omics data, to obtain a better consensus between existing extraction algorithms. It further provides guidelines for the development of the next-generation of data contextualization methods.
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