ArticlePLoS computational biology2012
Reconstruction of genome-scale active metabolic networks for 69 human cell types and 16 cancer types using INIT.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 235 papers.
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Who cites it
235 citing papers in PubMed.
- XomicsToModel: omics data integration and generation of thermodynamically consistent metabolic models.Nature protocols · 2026Article
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- Flux sampling and context-specific genome-scale metabolic models for biotechnological applications.Trends in biotechnology · 2026Review
- Modeling tissue-specific Drosophila metabolism identifies high sugar diet-induced metabolic dysregulation in muscle at reaction and pathway levels.Nature communications · 2026Article
- Co-Metabolic Network Reveals the Metabolic Mechanism of Host-Microbiota Interplay in Colorectal Cancer.Metabolites · 2026Article
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- 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
- Multi-omic data integration and exploiting metabolic models using systems biology approach increase precision in subtyping and early diagnosis of cancer.Quantitative biology (Beijing, China) · 2025Article
- Optimization-based framework with flux balance analysis (FBA) and metabolic pathway analysis (MPA) for identifying metabolic objective functions.PLoS computational biology · 2025Article
- Genome-Scale Metabolic Modeling Identifies Synergistic Metabolites that Enhance 5-Fluorouracil Efficacy in Colon Cancer.Iranian biomedical journal · 2025Article
- Longitudinal big biological data in the AI era.Molecular systems biology · 2025Review
- ThermOptCobra: Thermodynamically optimal construction and analysis of metabolic networks for reliable phenotype predictions.iScience · 2025Article
- Artificial intelligence and computational methods in human metabolism research: A comprehensive survey.Journal of pharmaceutical analysis · 2025Review
- Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation.NPJ systems biology and applications · 2025Article
- Moving from genome-scale to community-scale metabolic models for the human gut microbiome.Nature microbiology · 2025Review
- MiNEApy: enhancing enrichment network analysis in metabolic networks.Bioinformatics (Oxford, England) · 2025Article
- Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025Review
175 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
Development of high throughput analytical methods has given physicians the potential access to extensive and patient-specific data sets, such as gene sequences, gene expression profiles or metabolite footprints. This opens for a new approach in health care, which is both personalized and based on system-level analysis. Genome-scale metabolic networks provide a mechanistic description of the relationships between different genes, which is valuable for the analysis and interpretation of large experimental data-sets. Here we describe the generation of genome-scale active metabolic networks for 69 different cell types and 16 cancer types using the INIT (Integrative Network Inference for Tissues) algorithm. The INIT algorithm uses cell type specific information about protein abundances contained in the Human Proteome Atlas as the main source of evidence. The generated models constitute the first step towards establishing a Human Metabolic Atlas, which will be a comprehensive description (accessible online) of the metabolism of different human cell types, and will allow for tissue-level and organism-level simulations in order to achieve a better understanding of complex diseases. A comparative analysis between the active metabolic networks of cancer types and healthy cell types allowed for identification of cancer-specific metabolic features that constitute generic potential drug targets for cancer treatment.
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