ReviewACS synthetic biology2023
Machine Learning-Enabled Genome Mining and Bioactivity Prediction of Natural Products.
Review in ACS synthetic biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed.
- Accelerating natural product discovery, characterization and engineering by biofoundries.Natural product reports · 2026Review
- Artificial intelligence-driven advancements in agricultural biotechnology.Journal, genetic engineering & biotechnology · 2026Review
- Advances in tools, strategies, and applications of mining of microbial genomes for novel antimicrobials: a comprehensive review.Folia microbiologica · 2026Review
- Nature meets machine: the AI renaissance in natural product drug discovery.Natural products and bioprospecting · 2026Review
- Advances in natural product discovery: strategies, technologies, and insights.Natural products and bioprospecting · 2026Review
- NPASS database update 2026: comprehensive quantitative composition, bioactivity, and ADME-Tox data of natural products for biomedical research.Nucleic acids research · 2026Article
- MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis.Nucleic acids research · 2026Article
- AI-enabled fungal biomanufacturing: from genome mining to the artificial intelligence virtual cell.Mycology · 2026Review
- Natural products against Babesiosis: active compounds, molecular mechanisms, application limitations and translational development.Frontiers in cellular and infection microbiology · 2026Review
- Machine learning reveals targets ofFrontiers in immunology · 2026Article
- Unveiling the landscape of prokaryotic global regulators through deep protein language models.mSystems · 2025Article
- Advances in the microbial biosynthesis of therapeutic terpenoids.Current opinion in biotechnology · 2025Review
- Recent strategies and methodological advances for microbial natural product research in the post-genomics era.Archives of microbiology · 2025Review
- ElixirSeeker: A Machine Learning Framework Utilizing Fusion Molecular Fingerprints for the Discovery of Lifespan-Extending Compounds.Aging cell · 2025Article
- Article
- Enhancing rufomycin production by CRISPR/Cas9-based genome editing and promoter engineering inSynthetic and systems biotechnology · 2025Article
- From data to discovery: leveraging big data in plant natural products biosynthesis research.The Plant journal : for cell and molecular biology · 2025Review
- Synthetic Biology in Natural Product Biosynthesis.Chemical reviews · 2025Review
- Advances in the biological production of sugar alcohols from biomass-derived xylose.World journal of microbiology & biotechnology · 2025Review
- Self-resistance-gene-guided, high-throughput automated genome mining of bioactive natural products from Streptomyces.Cell systems · 2025Article
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
Natural products (NPs) produced by microorganisms and plants are a major source of drugs, herbicides, and fungicides. Thanks to recent advances in DNA sequencing, bioinformatics, and genome mining tools, a vast amount of data on NP biosynthesis has been generated over the years, which has been increasingly exploited to develop machine learning (ML) tools for NP discovery. In this review, we discuss the latest advances in developing and applying ML tools for exploring the potential NPs that can be encoded by genomic language and predicting the types of bioactivities of NPs. We also examine the technical challenges associated with the development and application of ML tools for NP research.
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.