OIC-COMSTECH in Collaboration with ICGEB Organize international workshop

Abstract

Next-generation sequencing (NGS) has revolutionized genomics by enabling the mass production of high-resolution biological data. However, the enormous volume, complexity, and heterogeneity of this data pose major challenges in terms of storage, processing, and interpretation. The complexity of the field means that it is necessary to maintain an appropriate pace in the training of qualified personnel. Artificial intelligence (AI), and more specifically machine learning and deep learning, is therefore an essential tool for meeting these challenges.

Objectifs

Mastering bioinformatics tools and pipelines by training trainers;
Learning how to integrate AI algorithms for processing, aligning, and annotating genomic data;
Implement predictive models to identify variants, genes, or molecular signatures;
Know how to combine genomic data with other sources (transcriptomics, proteomics, clinical data);
Train participants to design and evaluate new algorithms for NGS analysis.

Key Topics:

1: AI on RNA-SEQ data

2: Local AI tools,

3: AI on Variant Calling data

4: AI on Metagenomic data

Target audiences: Bioinformaticians; PhD students; Researchers; Biotechnologists; and clinicians with a background in NGS Data analysis in OIC member states.

Profil of trainers:

Prof. Dr. Silvano PIAZZA

Prof Silvano is a distinguished researcher, and devoted scientist; Group Leader, Computational Biology at International Centre for Genetic Engineering and Biotechnology (ICGEB, Trieste Italy). He carried on by the Bioinformatics research unit is focused on extensively using and interpreting High-throughput analysis of genomic profiles used to discover molecular patterns, both in normal biological processes and in disease states. The research unit together with external collaborators (from both Italian and international institutions), has demonstrated that the synergistic use of genomic data, biological experiments and bioinformatics analysis might not only further the understanding of the processes involved in several diseases and in particular in cancer progression, but also provide lists of molecules with the potential to be incorporated in clinical settings. Nevertheless, with the massive amount, diversity, and availability of genomic datasets, bioinformatics research faces the challenge to integrate all of these source of information. For these reasons, the unit is particularly interested in integrated approaches because they are the key to understanding the complexity underlying the diseases, thus leading to the development of new therapies and diagnostic tools.

Dr Waseem Haider

Dr. Haider is a Professor of Bioinformatics at COMSATS University Islamabad (Pakistan), where he leads the Next Generation Sequencing Research Group (NGSRG) within the Computational Biology and Bioinformatics Group (CBBG). With over two decades of distinguished service, he is recognized as an accomplished researcher and trainer in data analysis, Next-Generation Sequencing (NGS), and Machine Learning (ML).

His research group works across diverse NGS domains including genome, exome, transcriptome (RNA-Seq), and metagenomics, as well as Artificial Intelligence applications involving Machine Learning, Deep Learning, Forecasting, and Language Models (LMs). Together with his students, Dr. Haider, also founded Next Gen Solutions (NGS), through which they have trained more than 2,000 researchers and students in hands-on data analysis workshops held at prestigious institutions in Pakistan and abroad. The proceeds from these training programs are dedicated to social welfare initiatives.

Registration link: Click Here

Deadline for application: November 7^th , 2025

Focal Person:

Prof. Dr. Waseem Haider, CUI Islamabad.
Email: haider.waseem@gmail.com

Contact Person:

Dr Akim Socohou Moutala
Senior Program Manager (OIC-COMSTECH)
Email: akim@comstech.org