ReviewCell2015
Using Genome-scale Models to Predict Biological Capabilities.
Review in Cell, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 369 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
369 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-scale metabolic modeling reveals increased reliance on valine catabolism in clinical isolates of Klebsiella pneumoniae.NPJ systems biology and applications · 2022Pooled it
- Endothelial SLC25A13 links glutamine metabolism to angiogenesis.EMBO molecular medicine · 2026Article
- Applications of synthetic biology in biomedicine.Molecular biomedicine · 2026Review
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Transcriptome-Integrated Metabolic Modeling Identifies Candidate Metabolic Adjuvants in Antibiotic-ResistantAntibiotics (Basel, Switzerland) · 2026Article
- Environmental formermSystems · 2026Article
- Annotating the pangenome reveals the diversity in the genetic basis for metabolic enzymes.Science advances · 2026Article
- Integrating Genome-Scale Metabolic Modeling with Machine Learning Improves Gene Essentiality Prediction in Triple-Negative Breast Cancer.International journal of molecular sciences · 2026Article
- Predictive Algal Systems Biology: Integrating Omics, Genome-Scale Metabolic Models, and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Review
- Evaluating completeness, coherence, and consistency of genome-scale function annotations.Briefings in bioinformatics · 2026Review
- Hypergraph learning with multi-dimensional metabolite feature extractions and static-dynamic attention mechanisms to fill missing reactions in metabolic networks.Briefings in bioinformatics · 2026Article
- Pre-implantation embryo metabolism identified by PEMA reveals endogenous lactate insufficiency contributes to pre-implantation development arrest.Fundamental research · 2026Article
- Incorporation of Cryptic Plasmid Energetics Improves Genome-Scale Metabolic Predictions in Probiotic E. coli Nissle 1917.Microbial biotechnology · 2026Article
- Comparing the ability of embedding methods on metabolic hypergraphs for capturing taxonomy-based features.Algorithms for molecular biology : AMB · 2026Article
- Multi-strain analysis ofmSystems · 2026Article
- Gut microbial metabolic disorder in depression: insights from computational modeling and mediation analysis.BMC microbiology · 2026Article
- A Novel Topology-Based Candidate Reaction Prediction Approach for Gap-Fillings of Genome-Scale Metabolic Models.Metabolites · 2026Article
- Whole-cell modeling predicts alternative proteome allocation strategies in the archaeon Methanococcus maripaludis.Scientific reports · 2026Article
- Using TraDIS as a complementary approach to long term evolution for mapping adaptive mutations in Escherichia coli.PLoS genetics · 2026Article
- Reduced glutathione levels inmSystems · 2026Article
309 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellular growth capabilities on various substrates and the effect of gene knockouts at the genome scale. Thus, much interest has developed in understanding and applying these methods to areas such as metabolic engineering, antibiotic design, and organismal and enzyme evolution. This Primer will get you started.
Indexed as
Identifiers
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.