ReviewMetabolites2020
Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.
Review in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages.International journal of molecular sciences · 2020Pooled it
- Sustainable production of glutaric acid in microbial cell factories: Current advances and future prospects.Synthetic and systems biotechnology · 2026Review
- A Robust Isotope Ratio LC-MS/MS Workflow for High-Throughput Metabolic Profiling of Bacteria.Analytical chemistry · 2026Article
- Model-based inference of enzyme inhibitions from perturbation-induced metabolic dynamics.bioRxiv : the preprint server for biology · 2026Article
- Metabolic Overdrive in Elite Sport: A Systems Model of AMPK-mTOR Oscillation, NADInternational journal of molecular sciences · 2026Review
- Review
- Multi-omic network inference from time-series data.NPJ systems biology and applications · 2025Article
- Article
- Bridging Ethnobotanical Knowledge and Multi-Omics Approaches for Plant-Derived Natural Product Discovery.Metabolites · 2025Review
- A Guide to Metabolic Network Modeling for Plant Biology.Plants (Basel, Switzerland) · 2025Review
- Biotechnology systems engineering: preparing the next generation of bioengineers.Frontiers in systems biology · 2025Article
- MetaPhenotype: A Transferable Meta-Learning Model for Single-Cell Mass Spectrometry-Based Cell Phenotype Prediction Using Limited Number of Cells.Analytical chemistry · 2024Article
- Monitoring and modelling the glutamine metabolic pathway: a review and future perspectives.Metabolomics : Official journal of the Metabolomic Society · 2023Review
- Recent advances in mass spectrometry-based computational metabolomics.Current opinion in chemical biology · 2023Review
- Article
- Towards inferring absolute concentrations from relative abundance in time-course GC-MS metabolomics data.Molecular omics · 2023Article
- Towards advanced bioprocess optimization: A multiscale modelling approach.Computational and structural biotechnology journal · 2023Article
- Metabolomics and modelling approaches for systems metabolic engineering.Metabolic engineering communications · 2022Review
- The metabolomics of human aging: Advances, challenges, and opportunities.Science advances · 2022Review
- Kinetic and data-driven modeling of pancreatic β-cell central carbon metabolism and insulin secretion.PLoS computational biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Metabolic networks are regulated to ensure the dynamic adaptation of biochemical reaction fluxes to maintain cell homeostasis and optimal metabolic fitness in response to endogenous and exogenous perturbations. To this end, metabolism is tightly controlled by dynamic and intricate regulatory mechanisms involving allostery, enzyme abundance and post-translational modifications. The study of the molecular entities involved in these complex mechanisms has been boosted by the advent of high-throughput technologies. The so-called omics enable the quantification of the different molecular entities at different system layers, connecting the genotype with the phenotype. Therefore, the study of the overall behavior of a metabolic network and the omics data integration and analysis must be approached from a holistic perspective. Due to the close relationship between metabolism and cellular phenotype, metabolic modelling has emerged as a valuable tool to decipher the underlying mechanisms governing cell phenotype. Constraint-based modelling and kinetic modelling are among the most widely used methods to study cell metabolism at different scales, ranging from cells to tissues and organisms. These approaches enable integrating metabolomic data, among others, to enhance model predictive capabilities. In this review, we describe the current state of the art in metabolic modelling and discuss future perspectives and current challenges in the field.
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What OpenQuestion holds
Registered trials
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.