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Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi
by
Chiang, Chen-Yu
, Lin, Hsiao-Ching
, Tran, Phuong Nguyen
, Chen, Pao-Yang
, Yen, Ming-Ren
in
Algorithms
/ Antibiotics
/ Backup software
/ Bacteria
/ Bacteria - chemistry
/ Bacteria - genetics
/ Bacteria - metabolism
/ Bacterial genetics
/ Bacterial infections
/ Bioactive compounds
/ bioactive properties
/ Bioinformatics
/ Biological activity
/ Biological Products - metabolism
/ Biomedical and Life Sciences
/ biosynthesis
/ Biotechnology
/ Cancer
/ Computational Biology
/ Drug Resistance, Microbial - genetics
/ Enzymes
/ Fungi
/ Fungi - chemistry
/ Fungi - genetics
/ Fungi - metabolism
/ Gene clusters
/ Gene Duplication
/ Gene Transfer, Horizontal
/ Genes
/ genome mining
/ Genome, Microbial - genetics
/ Genomes
/ Genomics
/ Hypotheses
/ Life Sciences
/ Metabolites
/ Microbial Genetics and Genomics
/ Microbiology
/ Mini-Review
/ Mining industry
/ multigene family
/ Multigene Family - genetics
/ Natural products
/ Plant metabolites
/ prediction
/ prioritization
/ screening
/ Secondary Metabolism - genetics
/ Secondary metabolites
2019
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Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi
by
Chiang, Chen-Yu
, Lin, Hsiao-Ching
, Tran, Phuong Nguyen
, Chen, Pao-Yang
, Yen, Ming-Ren
in
Algorithms
/ Antibiotics
/ Backup software
/ Bacteria
/ Bacteria - chemistry
/ Bacteria - genetics
/ Bacteria - metabolism
/ Bacterial genetics
/ Bacterial infections
/ Bioactive compounds
/ bioactive properties
/ Bioinformatics
/ Biological activity
/ Biological Products - metabolism
/ Biomedical and Life Sciences
/ biosynthesis
/ Biotechnology
/ Cancer
/ Computational Biology
/ Drug Resistance, Microbial - genetics
/ Enzymes
/ Fungi
/ Fungi - chemistry
/ Fungi - genetics
/ Fungi - metabolism
/ Gene clusters
/ Gene Duplication
/ Gene Transfer, Horizontal
/ Genes
/ genome mining
/ Genome, Microbial - genetics
/ Genomes
/ Genomics
/ Hypotheses
/ Life Sciences
/ Metabolites
/ Microbial Genetics and Genomics
/ Microbiology
/ Mini-Review
/ Mining industry
/ multigene family
/ Multigene Family - genetics
/ Natural products
/ Plant metabolites
/ prediction
/ prioritization
/ screening
/ Secondary Metabolism - genetics
/ Secondary metabolites
2019
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Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi
by
Chiang, Chen-Yu
, Lin, Hsiao-Ching
, Tran, Phuong Nguyen
, Chen, Pao-Yang
, Yen, Ming-Ren
in
Algorithms
/ Antibiotics
/ Backup software
/ Bacteria
/ Bacteria - chemistry
/ Bacteria - genetics
/ Bacteria - metabolism
/ Bacterial genetics
/ Bacterial infections
/ Bioactive compounds
/ bioactive properties
/ Bioinformatics
/ Biological activity
/ Biological Products - metabolism
/ Biomedical and Life Sciences
/ biosynthesis
/ Biotechnology
/ Cancer
/ Computational Biology
/ Drug Resistance, Microbial - genetics
/ Enzymes
/ Fungi
/ Fungi - chemistry
/ Fungi - genetics
/ Fungi - metabolism
/ Gene clusters
/ Gene Duplication
/ Gene Transfer, Horizontal
/ Genes
/ genome mining
/ Genome, Microbial - genetics
/ Genomes
/ Genomics
/ Hypotheses
/ Life Sciences
/ Metabolites
/ Microbial Genetics and Genomics
/ Microbiology
/ Mini-Review
/ Mining industry
/ multigene family
/ Multigene Family - genetics
/ Natural products
/ Plant metabolites
/ prediction
/ prioritization
/ screening
/ Secondary Metabolism - genetics
/ Secondary metabolites
2019
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Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi
Journal Article
Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi
2019
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Overview
Secondary metabolites (SM) produced by fungi and bacteria have long been of exceptional interest owing to their unique biomedical ramifications. The traditional discovery of new natural products that was mainly driven by bioactivity screening has now experienced a fresh new approach in the form of genome mining. Several bioinformatics tools have been continuously developed to detect potential biosynthetic gene clusters (BGCs) that are responsible for the production of SM. Although the principles underlying the computation of these tools have been discussed, the biological background is left underrated and ambiguous. In this review, we emphasize the biological hypotheses in BGC formation driven from the observations across genomes in bacteria and fungi, and provide a comprehensive list of updated algorithms/tools exclusively for BGC detection. Our review points to a direction that the biological hypotheses should be systematically incorporated into the BGC prediction and assist the prioritization of candidate BGC.
Publisher
Springer Berlin Heidelberg,Springer,Springer Nature B.V
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