held in conjunction with 

   ICCS 2025

(INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE)

Singapore 

  7-9 July, 2025

Artificial Intelligence Approaches for Network Analysis 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. The workshop will cover a wide range of topics related to AI-driven network analysis, including both theoretical advancements and practical applications. We encourage submissions that address novel methods, models, and applications of Artificial Intelligence in understanding and analyzing complex networks, with particular interest in the following areas: 

 1. AI Methods in Network Analysis: Machine learning and deep learning approaches for network data.; Graph neural networks and their applications in large-scale network analysis; Reinforcement learning in dynamic and adaptive networks; Probabilistic models and uncertainty quantification in network data; Evolutionary algorithms for network optimization problems. 

 2. Network Analysis in Bioinformatics: AI approaches for biological network modeling and analysis; Protein-protein interaction networks; Gene regulatory and metabolic networks; Network-based approaches for drug discovery and repurposing; Disease-gene association studies using network methods. 

 3. Network Geometry: Geometrical approaches to network structure and dynamics; Hyperbolic embeddings and their role in network inference; Geometric deep learning applied to network data; Applications of network geometry in biological and social networks. 

 4. Complex Network Theory and Applications: AI techniques for the analysis of social, biological, and technological networks; Community detection, influence propagation, and link prediction. • Dynamics on and of networks, including diffusion and epidemics; Multilayer and temporal network analysis.

 5. Scalable AI for Network Analysis: Efficient AI algorithms for large-scale and high-dimensional network data; Parallel and distributed AI techniques for network computation; Handling sparse, noisy, and incomplete network data.

 6. Applications in Real-World Domains: Applications of AI in bioinformatics, neuroscience, healthcare, and epidemiology; Network-based AI solutions in infrastructure, communication, and transportation systems; AI for social media, recommendation systems, and e-commerce networks. 

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.