ReviewMarine drugs2022
Targeted Large-Scale Genome Mining and Candidate Prioritization for Natural Product Discovery.
Review in Marine drugs, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Comparative Genome Mining ofMarine drugs · 2026Article
- Harnessing engineered cyanobacteria for next-generation therapeutics.Archives of microbiology · 2026Review
- Functional Characterization ofAntibiotics (Basel, Switzerland) · 2026Article
- Multi-omics approaches: transforming the landscape of natural product isolation.Functional & integrative genomics · 2025Review
- Genetically-modified activation strategy facilitates the discovery of sesquiterpene-derived metabolites fromSynthetic and systems biotechnology · 2025Article
- Last Decade Insights in Exploiting Marine Microorganisms as Sources of New Bioactive Natural Products.Marine drugs · 2025Review
- Exploration of diverse secondary metabolites from Penicillium brasilianum by co-culturing with Armillaria mellea.Applied microbiology and biotechnology · 2024Article
- Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design.ACS catalysis · 2023Review
- Genome Mining and Screening for Secondary Metabolite Production in the Endophytic FungusMicroorganisms · 2023Article
- Complete Genome Sequence Analysis ofMicroorganisms · 2023Article
- Mining and characterization of the PKS-NRPS hybrid for epicoccamide A: a mannosylated tetramate derivative from Epicoccum sp. CPCC 400996.Microbial cell factories · 2022Article
- Overview on Strategies and Assays for Antibiotic Discovery.Pharmaceuticals (Basel, Switzerland) · 2022Review
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
Large-scale genome-mining analyses have identified an enormous number of cryptic biosynthetic gene clusters (BGCs) as a great source of novel bioactive natural products. Given the sheer number of natural product (NP) candidates, effective strategies and computational methods are keys to choosing appropriate BGCs for further NP characterization and production. This review discusses genomics-based approaches for prioritizing candidate BGCs extracted from large-scale genomic data, by highlighting studies that have successfully produced compounds with high chemical novelty, novel biosynthesis pathway, and potent bioactivities. We group these studies based on their BGC-prioritization logics: detecting presence of resistance genes, use of phylogenomics analysis as a guide, and targeting for specific chemical structures. We also briefly comment on the different bioinformatics tools used in the field and examine practical considerations when employing a large-scale genome mining study.
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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.