Chemical and Biological resources for Toxicology and Toxicogenomics
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Owner/Developer: The Data Infrastructure for Chemical Safety & University of Maastricht (dixa)
01 October 2011
EU Framework Programme 7
This 3-day diXa course will give participants an overview of the chemical and biological resources that are available for researchers in the field of Toxicology and Toxicogenomics. The course is aimed at researchers and scientists from academia as well as Industry with an interest in toxicology, toxicogenomics and life sciences.
The Data Infrastructure for Chemical Safety (diXa) project works with past and current EU FP7 projects, developing Alternatives to Animal testing, to safeguard data for the future. diXa aims to develop a sustainable data infrastructure to capture all data produced by toxicogenomics projects in a standardized, harmonized and sustainable manner. The lack of such an infrastructure currently prevents innovative breakthroughs from meta-analyses of joint databases and systems modeling. The diXa Data Warehouse will link to other globally available chemical/toxicological databases and data bases on molecular data of human disease to facilitate interdisciplinary research.
Hands-on training, Lecture
Optional / Voluntary
Students, Researchers, Regulators and policy-makers, Teachers and educators, Managers, Scientific officers / Project managers
Academia, Industry, Governmental bodies, Contract Research Organizations (CROs), Consulting, SMEs
Continuing Professional Development
Substantial coverage (e.g. multiple modules)
|Details on the topic or technology covered:||
1. Industry drivers for advancement of in silico toxicology methods
2. ChEMBL - small molecule resources
3. Exploring genes and phenotypes with the Ensembl Genome Browser
4. The Protein Data Bank in Europe: bringing structure to biology
5. Exploring functional genomic data (ArrayExpress - Expression Altas - exercises
6. Toxicology and Toxicogenomics data in UniProt sequence database - exercises
7. Bite-sized EBI resources - hands-on
8. Introduction to the diXa project
10. Cross check of data quality control and initial data analysis; Genedata workflow demonstration
11.The robustness of pathway based predictive models
12. Construction of a predictive molecular network for DILI
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