ArticleNature communications2022
Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Mechanism-informed rules tunably balance novelty and feasibility of predicted enzymatic reactions.bioRxiv : the preprint server for biology · 2026Article
- In silico analysis and comparison of the metabolic capabilities of different organisms by reducing metabolic complexity.Microbiome · 2026Article
- Systematic design and evaluation of artificial COSynthetic and systems biotechnology · 2025Article
- Computational approaches to enzymatic reaction assignment: a review of methods, validations, and future directions.Briefings in bioinformatics · 2025Review
- Before LUCA: unearthing the chemical roots of metabolism.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- Enhancing tandem mass spectrometry-based metabolite annotation with online chemical labeling.Nature communications · 2025Article
- Designing pathways for bioproducing complex chemicals by combining tools for pathway extraction and ranking.Nature communications · 2025Article
- Microbes are life, the biological core ofmicroLife · 2025Article
- Unveiling Metabolic Engineering Strategies by Quantitative Heterologous Pathway Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota.NPJ systems biology and applications · 2024Article
- Back to the Future of Metabolism-Advances in the Discovery and Characterization of Unknown Biocatalytic Functions and Pathways.Life (Basel, Switzerland) · 2024Review
- From microbiome composition to functional engineering, one step at a time.Microbiology and molecular biology reviews : MMBR · 2023Review
- An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification.Journal of cheminformatics · 2023Article
- enviRule: an end-to-end system for automatic extraction of reaction patterns from environmental contaminant biotransformation pathways.Bioinformatics (Oxford, England) · 2023Article
- Redesigning plant specialized metabolism with supervised machine learning using publicly available reactome data.Computational and structural biotechnology journal · 2023Review
- Review
- Biosynthesis of plant hemostatic dencichine in Escherichia coli.Nature communications · 2022Article
- Complexity reduction and opportunities in the design, integration and intensification of biocatalytic processes for metabolite synthesis.Frontiers in bioengineering and biotechnology · 2022Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolic "dark matter" describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark matter of metabolism remains an open challenge that can be addressed globally and systematically by existing computational solutions. In this work, we use 489 generalized enzymatic reaction rules to map both known and unknown metabolic processes around a biochemical database of 1.5 million biological compounds. We predict over 5 million reactions and integrate nearly 2 million naturally and synthetically-derived compounds into the global network of biochemical knowledge, named ATLASx. ATLASx is available to researchers as a powerful online platform that supports the prediction and analysis of biochemical pathways and evaluates the biochemical vicinity of molecule classes ( https://lcsb-databases.epfl.ch/Atlas2 ).
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