1. Omics Data Science and Bioinformatics

This track focuses on the analysis and interpretation of high-throughput biological data, including genomics, transcriptomics, metagenomics, proteomics and other bioinformatics approaches.
This track is designed for researchers working with biological data, computational biology, biomedical datasets and data-driven approaches to molecular-level health research.

Possible topics include:

● genome and transcriptome analysis● metagenomics and microbiome research● single-cell and spatial omics● multi-omics integration● biomarker discovery● computational methods for biological data● reproducibility and benchmark datasets in bioinformatics

2. Structural Bioinformatics, Drug Design and Molecular Modelling

This track explores how computational methods are used to study molecular structures, protein function, interactions and therapeutic discovery.
This track connects molecular biology, chemistry, computational modelling and pharmaceutical research.

Possible topics include:

● structural bioinformatics● protein modelling and protein design● molecular docking and virtual screening● AI-assisted drug discovery● molecular dynamics● omputational approaches to drug repurposing● structure-based interpretation of disease mechanisms

3. Data Science for Diagnostics and Clinical Medicine

This track focuses on the use of data-driven methods in diagnosis, prognosis, clinical decision-making and patient care.
The track is relevant for clinicians, biomedical researchers, data scientists interested in how data science can support medical practice.

Possible topics include:

● machine learning for diagnostics● medical imaging and computer vision● clinical prediction models● digital biomarkers● decision-support systems● electronic health records and real-world clinical data● personalized and precision medicine● responsible AI in clinical settings

4. Public Health Intelligence

This track looks at how data science can support population health, epidemiology, surveillance, prevention and health system response.
This track is intended for public health researchers, epidemiologists, analysts, health officials and data scientists working with population-level health data.

Possible topics include:

● epidemiological modelling● infectious disease surveillance● wastewater and environmental surveillance● vaccination and prevention analytics● population health monitoring● health inequalities and vulnerable populations● public health dashboards and early warning systems● data-driven emergency preparedness

5. Data-Driven Policy and Health Systems

This track serves as a bridge between research, implementation and decision-making. It focuses on how data can inform policy, governance, resource allocation and health system reform.
This track is especially relevant for researchers, analysts, policy professionals, NGOs, public institutions and international organizations working on health systems and data-informed decision-making.

Possible topics include:

● evidence-based health policy● health system performance analytics● data for planning and prioritization● health financing and resource allocation● digital health governance● data ethics and responsible use of health data● policy evaluation and impact assessment● translating research into decisions