This course is part of the capacity building efforts in Bioinformatics and Biostatistics within the member institutions of the Pasteur Network.

With established large-scale biological data production in North Africa region, the ability to integrate various OMIC data types is increasingly crucial. Analysing data simultaneously provides insights that might not be achievable through individual data analyses and can lead to a more comprehensive understanding of biological systems.

We will present multiple methods allowing to integrate publicly available datasets with own data to deepen the understanding and gain further insight on the biological processes under study.

This course offers participants the necessary skills to collaborate effectively across disciplines, bridging the gap between experimental and computational biology.

Course outcomes

• Become familiar with the principles, flavours and challenges of OMIC integration.

• Understand fundamental data pre-processing concepts and their impact on integration, including missing values, and data distribution (normalization and scaling).

• Demystify the use of complex integrative methods through hands-on applying statistical approaches such as dimensionality reduction, and network-based methods.

• Develop an informed perspective on the key issues to make methodological choices according to the data available and the biological question(s).

• Apply and integrate good practices for data analysis in R/RStudio.

Date & place:

September 22-26, 2025. Institut Pasteur de Tunis. Bioinformatics training room.
Address: R5FH+7HJ, Av. Jugurtha, Tunis, Tunisia.
Phone: +216 71 783 022.

Target audience

This training is open to all scientists (students, postdocs, and researchers) involved in projects comprising various types of OMICs datasets.
No prior knowledge of integration methods for OMICs data is required. However, previous experience with any OMICs data analysis (transcriptomics, proteomics, epigenomics) is highly encouraged.

Scientific committee

• Natalia Pietrosemoli, Scientific coordinator. Bioinformatics and Biostatistics Hub, Institut Pasteur Paris
• Claudia Chica Bioinformatics and Biostatistics Hub, Institut Pasteur Paris
• Yosr Hamdi Biomedical Genomics and Oncogenetics Lab, Institut Pasteur Tunis & University Tunis el Manar.
• Alia Benkahla Laboratory of BioInformatics, bioMathematics, and bioStatistics, Institut Pasteur Tunis
• Kais Ghedira Laboratory of BioInformatics, bioMathematics, and bioStatistics, Institut Pasteur Tunis
• Cheikh Loucoubar Pôle Épidémiologie, Recherches Cliniques et Sciences des Données, Institut Pasteur Dakar

Teaching team

Alia Benkahla, Hicham Charoute, Claudia Chica, Yosr Hamdi, Oussema Khamessi, Oussema Souiai, Natalia Pietrosemoli, Emeline Perthame. Belonging to: Institut Pasteur Paris, Institut Pasteur Tunis, University Tunis el Manar and Institut Pasteur Morroco.

Prerequisites & work environment

Applicants must have familiarity with R/RStudio, including understanding of RStudio environment, R syntax, and package installation.
Basic coding experience is recommended.
Practicals of the course will only be offered in person, and will be implemented in R language/R studio.

Registration Modalities

Application deadline: May 11, 2025

Participant selection: end of May.
Due to the limited capacity, the organizing committee will carefully evaluate the registration forms and select participants based on the information provided. Previous experience in OMIC data analysis will be a key evaluation criterion.

Information and registration:

https://building-bioinformatics-pn.pasteur.cloud

Contact:

bioinfo-pn@pasteur.fr

Candidate, last day to submit an application: May 11, 2025
Candidate, last day to edit an application: May 11, 2025