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Nextcast: A software suite to analyse and model toxicogenomics data
The recent advancements in toxicogenomics have led to the availability of large omics data sets, representing the starting point for studying the exposure mechanism of action and identifying candidate biomarkers for toxicity prediction. The current lack of standard methods in data generation and ana...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956870/ https://www.ncbi.nlm.nih.gov/pubmed/35386103 http://dx.doi.org/10.1016/j.csbj.2022.03.014 |
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author | Serra, Angela Saarimäki, Laura Aliisa Pavel, Alisa del Giudice, Giusy Fratello, Michele Cattelani, Luca Federico, Antonio Laurino, Omar Marwah, Veer Singh Fortino, Vittorio Scala, Giovanni Sofia Kinaret, Pia Anneli Greco, Dario |
author_facet | Serra, Angela Saarimäki, Laura Aliisa Pavel, Alisa del Giudice, Giusy Fratello, Michele Cattelani, Luca Federico, Antonio Laurino, Omar Marwah, Veer Singh Fortino, Vittorio Scala, Giovanni Sofia Kinaret, Pia Anneli Greco, Dario |
author_sort | Serra, Angela |
collection | PubMed |
description | The recent advancements in toxicogenomics have led to the availability of large omics data sets, representing the starting point for studying the exposure mechanism of action and identifying candidate biomarkers for toxicity prediction. The current lack of standard methods in data generation and analysis hampers the full exploitation of toxicogenomics-based evidence in regulatory risk assessment. Moreover, the pipelines for the preprocessing and downstream analyses of toxicogenomic data sets can be quite challenging to implement. During the years, we have developed a number of software packages to address specific questions related to multiple steps of toxicogenomics data analysis and modelling. In this review we present the Nextcast software collection and discuss how its individual tools can be combined into efficient pipelines to answer specific biological questions. Nextcast components are of great support to the scientific community for analysing and interpreting large data sets for the toxicity evaluation of compounds in an unbiased, straightforward, and reliable manner. The Nextcast software suite is available at: ( https://github.com/fhaive/nextcast). |
format | Online Article Text |
id | pubmed-8956870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-89568702022-04-05 Nextcast: A software suite to analyse and model toxicogenomics data Serra, Angela Saarimäki, Laura Aliisa Pavel, Alisa del Giudice, Giusy Fratello, Michele Cattelani, Luca Federico, Antonio Laurino, Omar Marwah, Veer Singh Fortino, Vittorio Scala, Giovanni Sofia Kinaret, Pia Anneli Greco, Dario Comput Struct Biotechnol J Method Article The recent advancements in toxicogenomics have led to the availability of large omics data sets, representing the starting point for studying the exposure mechanism of action and identifying candidate biomarkers for toxicity prediction. The current lack of standard methods in data generation and analysis hampers the full exploitation of toxicogenomics-based evidence in regulatory risk assessment. Moreover, the pipelines for the preprocessing and downstream analyses of toxicogenomic data sets can be quite challenging to implement. During the years, we have developed a number of software packages to address specific questions related to multiple steps of toxicogenomics data analysis and modelling. In this review we present the Nextcast software collection and discuss how its individual tools can be combined into efficient pipelines to answer specific biological questions. Nextcast components are of great support to the scientific community for analysing and interpreting large data sets for the toxicity evaluation of compounds in an unbiased, straightforward, and reliable manner. The Nextcast software suite is available at: ( https://github.com/fhaive/nextcast). Research Network of Computational and Structural Biotechnology 2022-03-18 /pmc/articles/PMC8956870/ /pubmed/35386103 http://dx.doi.org/10.1016/j.csbj.2022.03.014 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Method Article Serra, Angela Saarimäki, Laura Aliisa Pavel, Alisa del Giudice, Giusy Fratello, Michele Cattelani, Luca Federico, Antonio Laurino, Omar Marwah, Veer Singh Fortino, Vittorio Scala, Giovanni Sofia Kinaret, Pia Anneli Greco, Dario Nextcast: A software suite to analyse and model toxicogenomics data |
title | Nextcast: A software suite to analyse and model toxicogenomics data |
title_full | Nextcast: A software suite to analyse and model toxicogenomics data |
title_fullStr | Nextcast: A software suite to analyse and model toxicogenomics data |
title_full_unstemmed | Nextcast: A software suite to analyse and model toxicogenomics data |
title_short | Nextcast: A software suite to analyse and model toxicogenomics data |
title_sort | nextcast: a software suite to analyse and model toxicogenomics data |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956870/ https://www.ncbi.nlm.nih.gov/pubmed/35386103 http://dx.doi.org/10.1016/j.csbj.2022.03.014 |
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