ReviewFrontiers in oncology2022
Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.
Review in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- MechAInistic: A Reviewer-Supervised Multi-Agent LLM System for Auditable Mechanistic Drug-Hypothesis Generation.bioRxiv : the preprint server for biology · 2026Article
- A scoping review of computational models on human glucose cerebral metabolism.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026Review
- Integrated multi-dimensional modeling of non-model bacteria identifies engineering targets for acarbose biosynthesis optimization.Cell reports methods · 2026Article
- Predictive Algal Systems Biology: Integrating Omics, Genome-Scale Metabolic Models, and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Review
- Mathematical Modeling in Cancer Metabolism: Tools for Translational Applications in Metabolism-Based Therapy.Advances in experimental medicine and biology · 2026Review
- A constraint-based framework for exploring the impact of multireaction dependencies on metabolic functions.NPJ systems biology and applications · 2025Article
- Article
- Unraveling the glycosphingolipid metabolism by leveraging transcriptome-weighted network analysis on neuroblastic tumors.Cancer & metabolism · 2024Article
- Integrating multi-omics to unravel host-microbiome interactions in inflammatory bowel disease.Cell reports. Medicine · 2024Review
- Kinetic Trajectories of Glucose Uptake in Single Cancer Cells Reveal a Drug-Induced Cell-State Change Within Hours of Drug Treatment.The journal of physical chemistry. B · 2024Article
- Adding metabolic tasks to human GEM models to improve the study of gene targets and their associated toxicities.Scientific reports · 2024Article
- Accounting for NAD Concentrations in Genome-Scale Metabolic Models Captures Important Metabolic Alterations in NAD-Depleted Systems.Biomolecules · 2024Article
- Applying Proteomics and Computational Approaches to Identify Novel Targets in Blast-Associated Post-Traumatic Epilepsy.International journal of molecular sciences · 2024Article
- Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics.Microbiology spectrum · 2024Article
- "Energetics of the outer retina I: Estimates of nutrient exchange and ATP generation".PloS one · 2024Article
- Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The influence of metabolism on signaling, epigenetic markers, and transcription is highly complex yet important for understanding cancer physiology. Despite the development of high-resolution multi-omics technologies, it is difficult to infer metabolic activity from these indirect measurements. Fortunately, genome-scale metabolic models and constraint-based modeling provide a systems biology framework to investigate the metabolic states and define the genotype-phenotype associations by integrations of multi-omics data. Constraint-Based Reconstruction and Analysis (COBRA) methods are used to build and simulate metabolic networks using mathematical representations of biochemical reactions, gene-protein reaction associations, and physiological and biochemical constraints. These methods have led to advancements in metabolic reconstruction, network analysis, perturbation studies as well as prediction of metabolic state. Most computational tools for performing these analyses are written for MATLAB, a proprietary software. In order to increase accessibility and handle more complex datasets and models, community efforts have started to develop similar open-source tools in Python. To date there is a comprehensive set of tools in Python to perform various flux analyses and visualizations; however, there are still missing algorithms in some key areas. This review summarizes the availability of Python software for several components of COBRA methods and their applications in cancer metabolism. These tools are evolving rapidly and should offer a readily accessible, versatile way to model the intricacies of cancer metabolism for identifying cancer-specific metabolic features that constitute potential drug targets.
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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.