Nextcast

Nextcast provides a modular framework for processing and analyzing toxicogenomics data to explore exposure mechanisms and identify candidate biomarkers for regulatory toxicology.


Key Features:

  • Data Analysis and Modeling: Processes and analyzes toxicogenomics datasets to explore exposure mechanisms and identify candidate biomarkers.
  • Pipeline Integration: Integrates multiple software packages into modular pipelines that can be customized to answer specific biological questions.
  • Standardization Support: Implements standardization and reproducibility measures to strengthen toxicogenomics evidence for regulatory risk assessment.

Scientific Applications:

  • Interpretation of Toxicogenomics Data: Interprets large toxicogenomics datasets across analysis stages from preprocessing to downstream analyses.
  • Biomarker Identification and Mechanism Elucidation: Enables unbiased evaluation of compound toxicity and identification of candidate biomarkers to elucidate exposure mechanisms.
  • Regulatory Assessment and Predictive Toxicology: Supports regulatory risk assessments and predictive toxicological studies through standardized, reproducible analyses.

Methodology:

Implements specialized software components to process and analyze toxicogenomics data, integrate multiple packages into modular pipelines, and perform analyses from preprocessing to downstream stages with emphasis on standardization and reproducibility.

Topics

Details

License:
Not licensed
Cost:
Free of charge
Tool Type:
workflow
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R
Added:
7/26/2022
Last Updated:
11/24/2024

Operations

Publications

Serra A, Saarimäki LA, Pavel A, del Giudice G, Fratello M, Cattelani L, Federico A, Laurino O, Marwah VS, Fortino V, Scala G, Sofia Kinaret PA, Greco D. Nextcast: A software suite to analyse and model toxicogenomics data. Computational and Structural Biotechnology Journal. 2022;20:1413-1426. doi:10.1016/j.csbj.2022.03.014. PMID:35386103. PMCID:PMC8956870.

PMID: 35386103
PMCID: PMC8956870
Funding: - H2020: 814426, 814572 - Academy of Finland: 322761

Links