CONDOP: an R package for CONdition-Dependent Operon Predictions

Vittorio Fortino; Roberto Tagliaferri; Dario Greco

doi:10.1093/bioinformatics/btw330

CONDOP: an R package for CONdition-Dependent Operon Predictions

Vittorio Fortino, Roberto Tagliaferri, Dario Greco

Research output: Contribution to journal › Article › Scientific › peer-review

4 Citations (Scopus)

Abstract

The use of high-throughput RNA sequencing to predict dynamic operon structures in prokaryotic genomes has recently gained popularity in bioinformatics. We provide the R implementation of a novel method that uses transcriptomic features extracted from RNA-seq transcriptome profiles to develop ensemble classifiers for condition-dependent operon predictions. The CONDOP package provides a deeper insight into RNA-seq data analysis and allows scientists to highlight the operon organization in the context of transcriptional regulation with a few lines of code.

AVAILABILITY AND IMPLEMENTATION: CONDOP is implemented in R and is freely available at CRAN.

CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

Original language	English
Pages (from-to)	3199-3200
Number of pages	2
Journal	Bioinformatics
Volume	32
Issue number	20
DOIs	https://doi.org/10.1093/bioinformatics/btw330
Publication status	Published - 15 Oct 2016
Externally published	Yes
Publication type	A1 Journal article-refereed

Keywords

High-Throughput Nucleotide Sequencing
Operon
RNA
Sequence Analysis, RNA
Software

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10.1093/bioinformatics/btw330

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title = "CONDOP: an R package for CONdition-Dependent Operon Predictions",

abstract = "The use of high-throughput RNA sequencing to predict dynamic operon structures in prokaryotic genomes has recently gained popularity in bioinformatics. We provide the R implementation of a novel method that uses transcriptomic features extracted from RNA-seq transcriptome profiles to develop ensemble classifiers for condition-dependent operon predictions. The CONDOP package provides a deeper insight into RNA-seq data analysis and allows scientists to highlight the operon organization in the context of transcriptional regulation with a few lines of code.AVAILABILITY AND IMPLEMENTATION: CONDOP is implemented in R and is freely available at CRAN.CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.",

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author = "Vittorio Fortino and Roberto Tagliaferri and Dario Greco",

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doi = "10.1093/bioinformatics/btw330",

language = "English",

volume = "32",

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AU - Fortino, Vittorio

AU - Tagliaferri, Roberto

AU - Greco, Dario

PY - 2016/10/15

Y1 - 2016/10/15

N2 - The use of high-throughput RNA sequencing to predict dynamic operon structures in prokaryotic genomes has recently gained popularity in bioinformatics. We provide the R implementation of a novel method that uses transcriptomic features extracted from RNA-seq transcriptome profiles to develop ensemble classifiers for condition-dependent operon predictions. The CONDOP package provides a deeper insight into RNA-seq data analysis and allows scientists to highlight the operon organization in the context of transcriptional regulation with a few lines of code.AVAILABILITY AND IMPLEMENTATION: CONDOP is implemented in R and is freely available at CRAN.CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

AB - The use of high-throughput RNA sequencing to predict dynamic operon structures in prokaryotic genomes has recently gained popularity in bioinformatics. We provide the R implementation of a novel method that uses transcriptomic features extracted from RNA-seq transcriptome profiles to develop ensemble classifiers for condition-dependent operon predictions. The CONDOP package provides a deeper insight into RNA-seq data analysis and allows scientists to highlight the operon organization in the context of transcriptional regulation with a few lines of code.AVAILABILITY AND IMPLEMENTATION: CONDOP is implemented in R and is freely available at CRAN.CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

KW - High-Throughput Nucleotide Sequencing

KW - Operon

KW - RNA

KW - Sequence Analysis, RNA

KW - Software

U2 - 10.1093/bioinformatics/btw330

DO - 10.1093/bioinformatics/btw330

M3 - Article

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SN - 1367-4803

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SP - 3199

EP - 3200

JO - Bioinformatics

JF - Bioinformatics

IS - 20

ER -

CONDOP: an R package for CONdition-Dependent Operon Predictions

Abstract

Keywords

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