held in conjunction with 

   ICCS 2026

(INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE)

29 June - 1 July 2026 • DESY • Hamburg • Germany

The AI4NetBio Workshop – Artificial Intelligence for Network Analysis in Biology and Beyond aims to bring together researchers and practitioners working at the intersection of AI methods and network analysis, with a special focus on bioinformatics and biomedical applications.

We welcome contributions that present novel algorithms, models, and applications of AI to understand, model, and analyze complex networks across multiple domains. Both theoretical advances and practical implementations are encouraged.

Topics of interest include, but are not limited to:

AI Methods for Network Analysis:

Machine and deep learning for network data; graph neural networks (GNNs); reinforcement learning in dynamic networks; probabilistic and evolutionary models; uncertainty quantification.

Network Analysis in Bioinformatics:

Modeling of protein–protein interaction, gene regulatory and metabolic networks; disease–gene association studies; network-based approaches for drug discovery and repurposing.

Network Geometry & Representation Learning:

Hyperbolic embeddings; geometric deep learning; applications in biological and social networks.

Complex Network Theory and Applications:

Community detection, link prediction, influence propagation; dynamics on and of networks (diffusion, epidemics); multilayer and temporal networks.

Scalable AI for Large Networks:

Parallel and distributed AI techniques; handling high-dimensional, sparse, or noisy data.

Applications in Real-World Domains:

Bioinformatics, neuroscience, and healthcare; network-based AI in infrastructure, communication, and transportation systems; AI for social media and recommendation networks.

Why attend?

Network science has become a cornerstone for studying complex biological, biomedical, and clinical systems. Combined with AI, it enables integrative modeling from genomics to connectomics, supports drug repurposing, and enhances computational medicine through interpretable and causal machine learning.

The workshop aims to foster interdisciplinary dialogue between the communities of AI in healthcare and network/pathway analysis, promoting transparency, trust, and innovation in computational biology and medicine.

We invite the submission of original research papers, case studies, and tool presentations on these topics.

TOPICS OF INTEREST

The workshop is seeking original research papers presenting applications of parallel and high performance computing to biology and medicine. Topics of interest include, but are not limited to:

•        Network-based bioinformatics methods;

•        Networks-based applications in computational biology, genomics, medicine, and healthcare;

•        Graph representation learning for visualizing and interpreting biological and biomedical data;

•        Bioinformatics methods for network-based analysis and visualization;

•        Network-based modelling and analysis of complex diseases;

•      Complex network models for structure and function analysis;

•      Network models in epidemiology;

•       Next-generation network science;

•        Artificial intelligence for network models of complex diseases;

•        Applications of deep learning approaches in computational biology, genomics, medicine, and healthcare;

•        Networks Alignment;

•        Complex Prediction;

•        Network Embedding;

•        Pathways Analysis;

•        Interactomics databases;

•        Pathways databases;

•        Multilayer Network.

INTEREST TO ICCS COMMUNITY

This workshop aims to bring together researchers and practitioners working on various aspects of network analysis, with a particular focus on the intersection of AI methods and network-based problems in bioinformatics and other relevant fields.