antiSMASH statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Secondary metabolite biosynthetic pathways chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

antiSMASH specifications

Information


Unique identifier OMICS_09209
Name antiSMASH
Alternative name antibiotics & Secondary Metabolite Analysis Shell
Software type Package/Module
Interface Command line interface, Application programming interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Version 4.0.2
Stability Stable
Source code URL https://dl.secondarymetabolites.org/releases/4.0.2/antismash-4.0.2.tar.gz
Maintained Yes

Download


Versioning


Add your version

Additional information


http://docs.antismash.secondarymetabolites.org/

Information


Unique identifier OMICS_09209
Name antiSMASH
Alternative name antibiotics & Secondary Metabolite Analysis Shell
Interface Web user interface
Restrictions to use None
Programming languages Python
Computer skills Basic
Version 4.0
Stability Stable
Maintained Yes

Additional information


http://docs.antismash.secondarymetabolites.org/

Publications for antibiotics & Secondary Metabolite Analysis Shell

antiSMASH in publications

 (594)
PMCID: 5958101
PMID: 29773797
DOI: 10.1038/s41467-018-04364-9

[…] species of the genus sarocladium, because ani results were below 97%. all comparison with other species gives results of around 80% ani. we propose the name sarocladium schorii for this organism., antismash analysis suggested the presence of at least 39 secondary metabolite bgc (supplementary fig. ). basic local alignment search tool (blast) searching using the previously identified aspks1 […]

PMCID: 5946483
PMID: 29747580
DOI: 10.1186/s12864-018-4739-1

[…] database []. the secretomes of 14 fungi in this study were identified by signalp 4.1 and tmhmm 2.0 []. core secondary metabolite (sm) genes and clusters were initially identified using antismash. cyps genes were identified with hmmer and then named using the cytochrome p450 homepage []., c. pseudoreteaudii was cultured on pdb medium with 1% (w/v) eucalyptus tissue (leaves of e. […]

PMCID: 5932044
PMID: 29720592
DOI: 10.1038/s41598-018-24921-y

[…] ectoine, indole melanine, two siderophores, four terpenes are sheared among the three species, whereby 3 to 5 bgcs are specific in each species (table , fig. ).table 7awhen the outputs of antismash showed >40% gene similarities, we putatively considered them as putative products; blocus is shown as start-end positions and scaffold no. (sxx means scaffold000xx); cas analysis using […]

PMCID: 5920191
PMID: 29700154
DOI: 10.1128/genomeA.00323-18

[…] software tool prokka (). the draft genome contains 11 rrna genes, 90 trna genes, 3,673 protein-encoding genes with function prediction, and 1,535 genes coding for hypothetical proteins., the tool antismash 4.0.0 () was used for the in silico identification of biosynthetic gene clusters (bgcs) corresponding to the production of specialized metabolites, and nine putative bgcs were identified., […]

PMCID: 5920192
PMID: 29700134
DOI: 10.1128/genomeA.00194-18

[…] g+c content of 66.3%. the genome is predicted to have 4,544 coding sequences (cdss), 72 trna genes, and 28 rrna genes. we identified various antibacterial genes in the genome of p. aquatile cr182t; antismash shell analysis () revealed that the genome harbors 9 gene clusters involved in the biosynthesis of lantipeptide, hserlactone, bacteriocin, terpene, and a nonribosomal peptide synthetase […]


To access a full list of publications, you will need to upgrade to our premium service.

antiSMASH institution(s)
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark; Leibniz Institute for Natural Product Research and Infection Biology––Hans-Knoll-Institute, Jena, Germany; Laboratory of Genetics, University of Wisconsin––Madison, Madison, WI, USA; Bioinformatics Group, Wageningen University, Wageningen, Netherlands; Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Warwick Integrative Synthetic Biology Centre, University of Warwick, Coventry, UK; Department of Chemical and Biomolecular Engineering & BioInformatics Research Center, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; Faculty of Sciences, University of Lisbon, Lisbon, Portugal; Kekule-Institute of Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Manchester Synthetic Biology Research Centre (SYNBIOCHEM), Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
antiSMASH funding source(s)
Supported by Novo Nordisk Foundation; The Netherlands Organization for Scientific Research (NWO) VENI Grant [863.15.002]; Graduate School for Experimental Plant Sciences (EPS); Ministry of Science, ICT and Future Planning through the National Research Foundation (NRF) of Korea [NRF- 2012M1A2A2026556]; International Leibniz Research School for Microbial and Molecular Interactions (ILRS), as part of the excellence graduate school Jena School for Microbial Communication (JSMC), supported by the Deutsche Forschungsgemeinschaft (DFG); Collaborative Research Centre ChemBioSys (CRC 1127 ChemBioSys), by the DFG; NIH National Research Service Award [T32 GM008505]; David and Lucile Packard Fellowship for Science and Engineering; Department of Chemistry at the University of Illinois at Urbana–Champaign Fellowship; NIH Chemical Biology Interface Training Program Fellowship [T32 GM070421]; Google Summer of Code grant; Warwick Integrative Synthetic Biology Centre (WISB), and Manchester Synthetic Biology Research Centre (SYNBIOCHEM) funded under the UK Research Councils’ ’Synthetic Biology for Growth’ programme [BB/M017982/1 (WISB), BB/M017702/1 (SYNBIOCHEM)].

antiSMASH review

star_border star_border star_border star_border star_border
star star star star star

sro

star_border star_border star_border star_border star_border
star star star star star
Desktop
Fast, accurate, versatile, quite precise! Best platform for BGCs prediction.