Tutorial on Reverse Engineering of Gene Regulatory Networks
A hands-on tutorial on inferring gene regulatory networks from transcriptomic data, covering the full analytical workflow from data preprocessing to network evaluation.
This tutorial is organized by Young InfoLife in collaboration with CIBB 2026.
- When Tuesday, September 1, 2026, afternoon
- Where Sapienza University of Rome
- Fee No registration fee
- Seats Limited availability
Registration for this tutorial is separate from CIBB 2026 registration and is not required to attend the main conference.
Abstract
The reverse engineering of biological networks from omics data is one of the central problems in systems biology and bioinformatics. In particular, the inference of gene regulatory networks from transcriptomic data involves reconstructing plausible regulatory relationships between genes from indirect measures of gene expression, obtained using technologies such as RNA-seq.
This problem is particularly relevant but also complex: transcriptomic datasets are often noisy, high-dimensional, and characterised by a number of genes far exceeding the number of available samples. Furthermore, the correct interpretation of the results requires a combination of biological, statistical, and computational expertise.
This tutorial is designed to guide participants through a complete reverse-engineering workflow, from data preparation to network evaluation, with an introductory and practical approach accessible even to those without prior experience in biological network inference.
Who should attend
This tutorial is designed for:
- PhD students and early-career researchers in bioinformatics, systems biology, computational biology, or related fields
- Researchers approaching gene regulatory network inference for the first time
- Participants of CIBB 2026 wishing to deepen their understanding of network inference methods before the main conference
No prior experience with gene regulatory networks is required. Familiarity with basic data analysis and scripting is recommended.
Learning outcomes
By the end of the tutorial, participants will be able to:
- Understand the structure of a transcriptomic dataset used for network inference
- Perform preprocessing and exploratory data analysis
- Apply computational methods for regulatory network inference, including correlation-based, mutual information-based, and regression-based approaches
- Evaluate the quality of inferred networks using metrics such as precision, recall, AUROC, and AUPRC
- Critically interpret the results and recognise the main limitations of reverse engineering from omics data
Program
Tuesday, September 1, 2026
| Time | Activity |
|---|---|
| TBA | Introduction - Biological and computational background: nodes, edges, and the main challenges of network inference |
| TBA | Data exploration and preprocessing - Data inspection, normalization, transformation, gene filtering, and exploratory analysis |
| TBA | Network inference - Application of reverse engineering methods |
| TBA | Network evaluation - Precision, recall, AUROC, AUPRC, and the limitations of accuracy in sparse biological networks |
| TBA | Discussion - Comparison of methodological choices and interpretation of inferred regulatory interactions |
Materials
The organizers will provide all materials required to follow the tutorial and reproduce the analysis, including:
- Slides introducing the biological background, the transcriptomic data, and the network inference methods
- Example transcriptomic datasets
- Scripts or notebooks for data preprocessing, network inference, and evaluation
- Step-by-step instructions for the hands-on activities
- A gold standard or reference network for comparison, where available
- Recordings of preparatory webinars, made available on the Young InfoLife YouTube channel
Materials may be shared before the event to allow participants to review background concepts, set up their working environment, and become familiar with the task.
Speakers
Dora Tortarolo
Università degli Studi di Torino
Grete Francesca Privitera
Università degli Studi di Catania
Roberto Pagliarini
Università degli Studi di Udine
Register
We are offering a free, hands-on pre-conference tutorial on reverse engineering of gene regulatory networks from transcriptomic data. Seats are limited.
To register, please fill in the form.
About CIBB 2026
This tutorial is organized as part of CIBB 2026, the 21st International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, taking place at Sapienza University of Rome on September 2-4, 2026.
Participants are warmly invited to attend the main conference. CIBB 2026 offers three days of keynote lectures, special sessions, and contributed talks spanning bioinformatics, biostatistics, medical informatics, and AI-driven biomedical research. Special registration rates are available for students and retired academics.