ArticleMolecules (Basel, Switzerland)2020
SYN-View: A Phylogeny-Based Synteny Exploration Tool for the Identification of Gene Clusters Linked to Antibiotic Resistance.
Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Benchmarking short and long read polishing tools for nanopore assemblies: achieving near-perfect genomes for outbreak isolates.BMC genomics · 2024Article
- Mechanism of Fumonisin Self-Resistance:Toxins · 2024Article
- Current Methods for Recombination Detection in Bacteria.International journal of molecular sciences · 2022Review
- Fungal secondary metabolites in food and pharmaceuticals in the era of multi-omics.Applied microbiology and biotechnology · 2022Review
- ARTS-DB: a database for antibiotic resistant targets.Nucleic acids research · 2022Article
- Genome mining for drug discovery: progress at the front end.Journal of industrial microbiology & biotechnology · 2021Review
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
The development of new antibacterial drugs has become one of the most important tasks of the century in order to overcome the posing threat of drug resistance in pathogenic bacteria. Many antibiotics originate from natural products produced by various microorganisms. Over the last decades, bioinformatical approaches have facilitated the discovery and characterization of these small compounds using genome mining methodologies. A key part of this process is the identification of the most promising biosynthetic gene clusters (BGCs), which encode novel natural products. In 2017, the Antibiotic Resistant Target Seeker (ARTS) was developed in order to enable an automated target-directed genome mining approach. ARTS identifies possible resistant target genes within antibiotic gene clusters, in order to detect promising BGCs encoding antibiotics with novel modes of action. Although ARTS can predict promising targets based on multiple criteria, it provides little information about the cluster structures of possible resistant genes. Here, we present SYN-view. Based on a phylogenetic approach, SYN-view allows for easy comparison of gene clusters of interest and distinguishing genes with regular housekeeping functions from genes functioning as antibiotic resistant targets. Our aim is to implement our proposed method into the ARTS web-server, further improving the target-directed genome mining strategy of the ARTS pipeline.
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Registered trials
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