| Autor: |
Angela Serra, Laura Aliisa Saarimäki, Alisa Pavel, Giusy del Giudice, Michele Fratello, Luca Cattelani, Antonio Federico, Omar Laurino, Veer Singh Marwah, Vittorio Fortino, Giovanni Scala, Pia Anneli Sofia Kinaret, Dario Greco |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 1413-1426 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2001-0370 |
| DOI: |
10.1016/j.csbj.2022.03.014 |
| Popis: |
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). |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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