ArticleSynthetic and systems biotechnology2016
FunGeneClusterS: Predicting fungal gene clusters from genome and transcriptome data.
Article in Synthetic and systems biotechnology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.
- Updating genome annotation for the microbial cell factory Aspergillus niger using gene co-expression networks.Nucleic acids research · 2019Pooled it
- Uncovering the transcriptional landscape of Fomes fomentarius during fungal-based material production through gene co-expression network analysis.Fungal biology and biotechnology · 2025Article
- The Cytotoxic Properties of Extreme Fungi's Bioactive Components-An Updated Metabolic and Omics Overview.Life (Basel, Switzerland) · 2023Review
- How to Completely Squeeze a Fungus-Advanced Genome Mining Tools for Novel Bioactive Substances.Pharmaceutics · 2022Review
- Machine learning from Pseudomonas aeruginosa transcriptomes identifies independently modulated sets of genes associated with known transcriptional regulators.Nucleic acids research · 2022Article
- Transcriptome and proteome profiling reveals complex adaptations of Candida parapsilosis cells assimilating hydroxyaromatic carbon sources.PLoS genetics · 2022Article
- Tracking of Diversity and Evolution in the Brown Rot FungiFrontiers in microbiology · 2022Article
- Article
- Beyond the Biosynthetic Gene Cluster Paradigm: Genome-Wide Coexpression Networks Connect Clustered and Unclustered Transcription Factors to Secondary Metabolic Pathways.Microbiology spectrum · 2021Article
- Colocality to Cofunctionality: Eukaryotic Gene Neighborhoods as a Resource for Function Discovery.Molecular biology and evolution · 2021Article
- TOUCAN: a framework for fungal biosynthetic gene cluster discovery.NAR genomics and bioinformatics · 2020Article
- A detailed in silico analysis of secondary metabolite biosynthesis clusters in the genome of the broad host range plant pathogenic fungus Sclerotinia sclerotiorum.BMC genomics · 2020Article
- Unearthing fungal chemodiversity and prospects for drug discovery.Current opinion in microbiology · 2019Review
- Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters.Briefings in bioinformatics · 2019Article
- Fungal secondary metabolism: regulation, function and drug discovery.Nature reviews. Microbiology · 2019Review
- Systems metabolic engineering for citric acid production by Aspergillus niger in the post-genomic era.Microbial cell factories · 2019Review
- Bioinformatics tools for the identification of gene clusters that biosynthesize specialized metabolites.Briefings in bioinformatics · 2018Review
- Review
- In silico prediction and characterization of secondary metabolite biosynthetic gene clusters in the wheat pathogen Zymoseptoria tritici.BMC genomics · 2017Article
- Development of fungal cell factories for the production of secondary metabolites: Linking genomics and metabolism.Synthetic and systems biotechnology · 2017Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSecondary metabolites of fungi are receiving an increasing amount of interest due to their prolific bioactivities and the fact that fungal biosynthesis of secondary metabolites often occurs from co-regulated and co-located gene clusters. This makes the gene clusters attractive for synthetic biology and industrial biotechnology applications. We have previously published a method for accurate prediction of clusters from genome and transcriptome data, which could also suggest cross-chemistry, however, this method was limited both in the number of parameters which could be adjusted as well as in user-friendliness. Furthermore, sensitivity to the transcriptome data required manual curation of the predictions. In the present work, we have aimed at improving these features.
resultsFunGeneClusterS is an improved implementation of our previous method with a graphical user interface for off- and on-line use. The new method adds options to adjust the size of the gene cluster(s) being sought as well as an option for the algorithm to be flexible with genes in the cluster which may not seem to be co-regulated with the remainder of the cluster. We have benchmarked the method using data from the well-studied
conclusionWe have developed FunGeneClusterS in a graphical implementation and made the method capable of adjustments to different datasets and target clusters. The method is versatile in that it can predict co-regulated clusters not limited to secondary metabolism. Our analysis of data has shown not only the validity of the method, but also strongly suggests that large parts of fungal primary metabolism and cellular functions are both co-regulated and co-located.
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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.