ArticleNucleic acids research2019
A deep learning genome-mining strategy for biosynthetic gene cluster prediction.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 201 papers, 1 of them a synthesis that pooled it.
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Who cites it
201 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Antimicrobial resistance crisis: could artificial intelligence be the solution?Military Medical Research · 2024Pooled it
- Temporal dynamics of gut biosynthetic gene clusters link persistent colonization and engraftment in fecal microbiota transplantation.Gut microbes · 2026Article
- Fast, flexible gene cluster family delineation with IGUA.Nucleic acids research · 2026Article
- Antibiotic-producing microorganisms: taxonomic diversity, screening strategies, and emerging and underexploited antibacterial targets.Archives of microbiology · 2026Review
- Large-scale discovery platform enables identification of peptides targeting drug-resistant candidiasis.Cell reports methods · 2026Article
- Comparative Genome Mining ofMarine drugs · 2026Article
- Biological applications and future perspectives of bioactive compounds as pig feed additives.Animal nutrition (Zhongguo xu mu shou yi xue hui) · 2026Review
- A guide to Direct Pathway Cloning (DiPaC) for natural product discovery.Essays in biochemistry · 2026Review
- Heterologous expression of NRPS and PKS pathways in Escherichia coli: from bottlenecks to biosynthetic platforms.Essays in biochemistry · 2026Review
- Siwa spring microbiomes as reservoirs of biosynthetic gene clusters: Unlocking natural product potential.World journal of microbiology & biotechnology · 2026Article
- Fine-grained structural classification of biosynthetic gene cluster-encoded products.Bioinformatics (Oxford, England) · 2026Article
- Genomic insights into the antarctic cyanobacterium Nostoc sp. CALU 1950.Archives of microbiology · 2026Article
- Resorcylic Acid Lactones and Isocoumarin Derivatives from the Marine-Associated Polar FungusMarine drugs · 2026Article
- Regulatory and metabolic control of microbial biosynthetic gene clusters.Communications biology · 2026Review
- Genomic insights into specialized and primary metabolism gene clusters in methicillin-resistant Staphylococcus aureus from Egyptian community settings.BMC genomics · 2026Article
- A foundation model enables prediction of natural product molecular properties, bioactivity, and structural similarity from biosynthetic gene cluster sequence.bioRxiv : the preprint server for biology · 2026Article
- Review
- Integrating host-microbiome multi-omics with machine learning: methods, benchmarks, and translational applications.Science China. Life sciences · 2026Review
- Microbial biobanking: safeguarding the tiny treasures for sustainable human welfare.Folia microbiologica · 2026Review
- Harnessing artificial intelligence for antimicrobial discovery and optimization.Current opinion in microbiology · 2026Review
141 more citing papers are in PubMed but not listed here.
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Natural products represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs, anticancer therapies, and immunomodulatory agents. These molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms, although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers reduced false positive rates in BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing machine-learning tools. We supplemented this with random forest classifiers that accurately predicted BGC product classes and potential chemical activity. Application of DeepBGC to bacterial genomes uncovered previously undetectable putative BGCs that may code for natural products with novel biologic activities. The improved accuracy and classification ability of DeepBGC represents a major addition to in-silico BGC identification.
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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.