ReviewBriefings in bioinformatics2025
Computational approaches to enzymatic reaction assignment: a review of methods, validations, and future directions.
Review in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Enhancing biocatalytic retrosynthesis with a graph-to-graph model.Chemical science · 2026Article
- Unbiased distance correlation with sample-size-aware confidence bounds for comparative omics network analysis.Frontiers in bioinformatics · 2026Article
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
Characterizing the proteins and molecules that underpin cellular metabolism is fundamental to advancing our understanding of biological processes. However, the rapidly expanding repertoire of newly identified proteins and metabolites presents significant challenges for experimental characterization and functional analysis. Computational approaches can be used to identify and elucidate catalytic relationships between enzymes and their substrates and provide powerful tools that support biological research and applications in biochemical engineering, and drug discovery. In this review, we describe the problem of reaction assignment for predicting enzymatic reactions leveraging structural, network, and high-throughput experimental data. Also considered are theoretical perspectives motivating the design of computational methods, available resources, and validation techniques. Current and future computational approaches for enzymatic reaction assignment are expected to advance in tandem with technologies for experimental analysis of metabolism, such as metabolomics, and flux-based methods, to expand our understanding of metabolism.
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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.