ArticleMethods in molecular biology (Clifton, N.J.)2013
Linking genome-scale metabolic modeling and genome annotation.
Article in Methods in molecular biology (Clifton, N.J.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- From FAIR to CURE: guidelines for computational models of biological systems.NPJ systems biology and applications · 2026Review
- A Protocol for the Automatic Construction of Highly Curated Genome-Scale Models of Human Metabolism.Bioengineering (Basel, Switzerland) · 2023Article
- Chaperonin Abundance Enhances Bacterial Fitness.Frontiers in molecular biosciences · 2021Article
- An engineering design approach to systems biology.Integrative biology : quantitative biosciences from nano to macro · 2017Review
- Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions.Nature communications · 2017Article
- Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models.PLoS computational biology · 2014Article
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
Genome-scale metabolic network reconstructions, assembled from annotated genomes, serve as a platform for integrating data from heterogeneous sources and generating hypotheses for further experimental validation. Implementing constraint-based modeling techniques such as flux balance analysis (FBA) on network reconstructions allows for interrogating metabolism at a systems level, which aids in identifying and rectifying gaps in knowledge. With genome sequences for various organisms from prokaryotes to eukaryotes becoming increasingly available, a significant bottleneck lies in the structural and functional annotation of these sequences. Using topologically based and biologically inspired metabolic network refinement, we can better characterize enzymatic functions present in an organism and link annotation of these functions to candidate transcripts; both steps can be experimentally validated.
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.