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Protocols

MIDDAS-M specifications

Information


Unique identifier OMICS_09243
Name MIDDAS-M
Interface Web user interface
Restrictions to use None
Computer skills Basic
Stability Stable
Maintained No

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Publication for MIDDAS-M

MIDDAS-M citations

 (5)
library_books

Heterologous Production of a Novel Cyclic Peptide Compound, KK 1, in Aspergillus oryzae

2018
Front Microbiol
PMCID: 5900794
PMID: 29686660
DOI: 10.3389/fmicb.2018.00690

[…] potential secondary metabolites in filamentous fungi. Moreover, another novel program, which is independent of the known sequence motifs of core genes for potential secondary metabolites and is named MIDDAS-M (motif-independent de novo detection algorithm for secondary metabolite biosynthetic gene clusters), has been constructed to predict the gene clusters required for secondary metabolite produc […]

library_books

Temperature during conidiation affects stress tolerance, pigmentation, and trypacidin accumulation in the conidia of the airborne pathogen Aspergillus fumigatus

2017
PLoS One
PMCID: 5423626
PMID: 28486558
DOI: 10.1371/journal.pone.0177050

[…] The gene clusters whose transcript levels are coordinately changed in the conidia cultured at 25°C or 45°C compared to those at 37°C were investigated using the MIDDAS-M algorithm []. Briefly, the induction ratio of genes at 25°C or 45°C over 37°C were evaluated in the logarithmic form with the base of 2 using the transcriptome data. After the Z-score normali […]

library_books

Are Some Fungal Volatile Organic Compounds (VOCs) Mycotoxins?

2015
Toxins
PMCID: 4591661
PMID: 26402705
DOI: 10.3390/toxins7093785

[…] other secondary metabolite gene clusters can be identified through gene expression patterns detected by EST, microarray or RNA-Seq data. Motif Independent Detection Algorithm for Secondary Products (MIDDAS-M) was developed based on this kind of transcriptome analysis. The MIDDAS-M program has the advantage that it detects only those secondary metabolite gene clusters that are expressed [].In summ […]

call_split

Motif independent de novo detection of secondary metabolite gene clusters—toward identification from filamentous fungi

2015
Front Microbiol
PMCID: 4419862
PMID: 25999925
DOI: 10.3389/fmicb.2015.00371
call_split See protocol

[…] les of producing and non-producing conditions and successively comparing these profiles should be an effective way to identify SMB gene clusters. Based on this idea, another motif-independent method, MIDDAS-M, was developed to detect gene clusters, whose component genes are co-regulated (Umemura et al., ). This method uses induction ratios of whole genes under compound producing over non-producing […]

library_books

Association of fungal secondary metabolism and sclerotial biology

2015
Front Microbiol
PMCID: 4329819
PMID: 25762985
DOI: 10.3389/fmicb.2015.00062

[…] bioinformatics, has provided researchers with an in silico approach for identifying potential secondary metabolic gene clusters (; ; ). Many of the prediction algorithms (e.g., SMURF, antiSMASH, and MIDDAS-M) in use are based on identification of core or “backbone” genes that encode enzymes such as a PKSs, NRPSs, or dimethylallyltryptophans (DMATs) as well as closely allied genes encoding “decora […]

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MIDDAS-M institution(s)
Bioproduction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Sapporo, Hokkaido, Japan; Bioproduction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan; Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan; Japan Biological Informatics Consortium, Koto-ku, Tokyo, Japan; Molecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan; Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan; Beltsville Agricultural Regional Research Center, Agricultural Research Service, USA Department of Agriculture, Beltsville, MD, USA; Department of Plant Biology and Pathology, Rutgers University, NB, NJ, USA

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