iPRESTO: integrated Prediction and Rigorous Exploration of biosynthetic Sub-clusters Tool

J.J.R. Louwen; S.A. Kautsar; S. van der Burg; M.H. Medema; J.J.J. van der Hooft

iPRESTO: integrated Prediction and Rigorous Exploration of biosynthetic Sub-clusters Tool

J.J.R. Louwen, S.A. Kautsar, S. van der Burg, M.H. Medema, J.J.J. van der Hooft

Research output: Non-textual form › Software

Abstract

iPRESTO (integrated Prediction and Rigorous Exploration of biosynthetic
Sub-clusters Tool) is a command line tool for the detection of gene sub-clusters in
a set of Biosynthetic Gene Clusters (BGCs) in GenBank format. BGCs are tokenised
by representing each gene as a combination of its Pfam domains, where subPfams
are used to increase resolution. Tokenised BGCs are filtered for redundancy
using similarity network with an Adjacency Index of domains as a distance metric.
For the detection of sub-clusters two methods are used: PRESTO-STAT, which is
based on the statistical algorithm from Del Carratore et al. (2019), and the
novel method PRESTO-TOP, which uses topic modelling with Latent Dirichlet
Allocation. The sub-clusters found with iPRESTO can then be linked to Natural
Product substructures.

Original language	English
Place of Publication	Wageningen
Publisher	Wageningen University & Research
Media of output	Online
Publication status	Published - 2022

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https://git.wageningenur.nl/bioinformatics/iPRESTO/Licence: GNU GPL

1 Article

iPRESTO: Automated discovery of biosynthetic sub-clusters linked to specific natural product substructures
Louwen, J. J. R., Kautsar, S. A., van der Burg, S., Medema, M. H. & van der Hooft, J. J. J., 9 Feb 2023, In: PLoS Computational Biology. 19, 2, p. e1010462
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
6 Citations (Scopus)

Data for iPRESTO: automated discovery of biosynthetic sub-clusters linked to specific natural product substructures
Louwen, J. J. R. (Creator), Kautsar, S. A. (Creator), van der Burg, S. (Creator), Medema, M. H. (Creator) & van der Hooft, J. J. J. (Creator), Wageningen University & Research, 2 Aug 2022
DOI: 10.5281/zenodo.6953656
Dataset

Cite this

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title = "iPRESTO: integrated Prediction and Rigorous Exploration of biosynthetic Sub-clusters Tool",

abstract = "iPRESTO (integrated Prediction and Rigorous Exploration of biosyntheticSub-clusters Tool) is a command line tool for the detection of gene sub-clusters ina set of Biosynthetic Gene Clusters (BGCs) in GenBank format. BGCs are tokenisedby representing each gene as a combination of its Pfam domains, where subPfamsare used to increase resolution. Tokenised BGCs are filtered for redundancyusing similarity network with an Adjacency Index of domains as a distance metric.For the detection of sub-clusters two methods are used: PRESTO-STAT, which isbased on the statistical algorithm from Del Carratore et al. (2019), and thenovel method PRESTO-TOP, which uses topic modelling with Latent DirichletAllocation. The sub-clusters found with iPRESTO can then be linked to NaturalProduct substructures.",

author = "J.J.R. Louwen and S.A. Kautsar and {van der Burg}, S. and M.H. Medema and {van der Hooft}, J.J.J.",

year = "2022",

language = "English",

publisher = "Wageningen University & Research",

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AU - van der Hooft, J.J.J.

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N2 - iPRESTO (integrated Prediction and Rigorous Exploration of biosyntheticSub-clusters Tool) is a command line tool for the detection of gene sub-clusters ina set of Biosynthetic Gene Clusters (BGCs) in GenBank format. BGCs are tokenisedby representing each gene as a combination of its Pfam domains, where subPfamsare used to increase resolution. Tokenised BGCs are filtered for redundancyusing similarity network with an Adjacency Index of domains as a distance metric.For the detection of sub-clusters two methods are used: PRESTO-STAT, which isbased on the statistical algorithm from Del Carratore et al. (2019), and thenovel method PRESTO-TOP, which uses topic modelling with Latent DirichletAllocation. The sub-clusters found with iPRESTO can then be linked to NaturalProduct substructures.

AB - iPRESTO (integrated Prediction and Rigorous Exploration of biosyntheticSub-clusters Tool) is a command line tool for the detection of gene sub-clusters ina set of Biosynthetic Gene Clusters (BGCs) in GenBank format. BGCs are tokenisedby representing each gene as a combination of its Pfam domains, where subPfamsare used to increase resolution. Tokenised BGCs are filtered for redundancyusing similarity network with an Adjacency Index of domains as a distance metric.For the detection of sub-clusters two methods are used: PRESTO-STAT, which isbased on the statistical algorithm from Del Carratore et al. (2019), and thenovel method PRESTO-TOP, which uses topic modelling with Latent DirichletAllocation. The sub-clusters found with iPRESTO can then be linked to NaturalProduct substructures.

M3 - Software

PB - Wageningen University & Research

CY - Wageningen

ER -

iPRESTO: integrated Prediction and Rigorous Exploration of biosynthetic Sub-clusters Tool

Abstract

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Research output

iPRESTO: Automated discovery of biosynthetic sub-clusters linked to specific natural product substructures

Datasets

Data for iPRESTO: automated discovery of biosynthetic sub-clusters linked to specific natural product substructures

Cite this