ArticlePLoS computational biology2021
Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Bacterial biosynthetic superclusters: emerging drivers of synergistic natural products against antimicrobial resistance.Essays in biochemistry · 2026Review
- Unified genomic and chemical representations enable bidirectional biosynthetic gene cluster and natural product retrieval.Scientific reports · 2026Article
- Accelerating natural product discovery with linked MS-genomics and language/transformer-based models.npj antimicrobials and resistance · 2026Article
- Large-scale multi-omics profiling reveals environmental and evolutionary drivers of fungal phylogeographic and metabolic diversity.Nature communications · 2026Article
- Green genes from blue greens: challenges and solutions to unlocking the potential of cyanobacteria in drug discovery.Natural product reports · 2026Review
- An integrative chemical and genomic similarity approach linking fungal secondary metabolites and biosynthetic gene clusters.Organic & biomolecular chemistry · 2026Article
- Rethinking Nature's Pharmacy: AI Era and Natural Product Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2026Review
- BiG-SCAPE 2.0 and BiG-SLiCE 2.0: scalable, accurate and interactive sequence clustering of metabolic gene clusters.Nature communications · 2026Article
- Advances in natural product discovery: strategies, technologies, and insights.Natural products and bioprospecting · 2026Review
- Phylogeny-Aware Metabologenomics Accurately Assigns Natural Products to Biosynthetic Gene Clusters.Microbial biotechnology · 2026Article
- Recent strategies and methodological advances for microbial natural product research in the post-genomics era.Archives of microbiology · 2025Review
- Sequence modeling tools to decode the biosynthetic diversity of the human microbiome.mSystems · 2025Review
- antiSMASH 8.0: extended gene cluster detection capabilities and analyses of chemistry, enzymology, and regulation.Nucleic acids research · 2025Article
- Effective data visualization strategies in untargeted metabolomics.Natural product reports · 2025Review
- Bridging Ethnobotanical Knowledge and Multi-Omics Approaches for Plant-Derived Natural Product Discovery.Metabolites · 2025Review
- Deciphering the biosynthetic potential of microbial genomes using a BGC language processing neural network model.Nucleic acids research · 2025Article
- Pattern-Based Genome Mining Guides Discovery of the Antibiotic Indanopyrrole A from a Marine Streptomycete.Journal of natural products · 2024Article
- Primed for Discovery.Biochemistry · 2024Review
- Pattern-based genome mining guides discovery of the antibiotic indanopyrrole A from a marine streptomycetef.bioRxiv : the preprint server for biology · 2024Article
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9 authors.
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Abstract
Specialised metabolites from microbial sources are well-known for their wide range of biomedical applications, particularly as antibiotics. When mining paired genomic and metabolomic data sets for novel specialised metabolites, establishing links between Biosynthetic Gene Clusters (BGCs) and metabolites represents a promising way of finding such novel chemistry. However, due to the lack of detailed biosynthetic knowledge for the majority of predicted BGCs, and the large number of possible combinations, this is not a simple task. This problem is becoming ever more pressing with the increased availability of paired omics data sets. Current tools are not effective at identifying valid links automatically, and manual verification is a considerable bottleneck in natural product research. We demonstrate that using multiple link-scoring functions together makes it easier to prioritise true links relative to others. Based on standardising a commonly used score, we introduce a new, more effective score, and introduce a novel score using an Input-Output Kernel Regression approach. Finally, we present NPLinker, a software framework to link genomic and metabolomic data. Results are verified using publicly available data sets that include validated links.
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