CIBB 2025
20th conference on Computational Intelligence methods for Bioinformatics and Biostatistics
September 10 - 12, 2025 in Milano, Italy
Special Session on:
Networks and Graph Neural Networks for Bridging Bioinformatics and Medicine
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ABSTRACT
ABSTRACT
We are delighted to announce a Special Session focusing on the transformative role of Networks and Graph Neural Networks (GNNs) in bridging bioinformatics and medicine. Recent advancements in network science and graph-based deep learning have revolutionized biomedical research.
Complex biological systems, including protein interactions, gene regulatory networks, and disease ontologies, can be effectively modelled using networks. Graph neural networks (GNNs) further provide a powerful framework to learn from these structures, enabling significant progress in disease classification, drug discovery, and precision medicine.
This special session aims to bring together researchers and practitioners from bioinformatics, medicine, and artificial intelligence to explore how networks and GNNs can bridge the gap between computational methods and clinical applications. We encourage contributions that develop new methodologies, provide novel applications, or highlight challenges and future directions in the field.
TOPICS
TOPICS
Submissions addressing, but not limited to, the following topics are warmly welcomed:
Network-based approaches in bioinformatics (e.g., protein-protein interaction networks, metabolic pathways, regulatory networks).
Graph Neural Networks in biomedical applications (e.g., disease diagnosis, drug repurposing, patient stratification)
Multi-omics data integration using networks and GNNs (i.e. utilizing networks and GNNs to combine genomics, proteomics, transcriptomics, and other data types for holistic insights)
Graph representation learning for medical imaging and diagnostics (i.e. cutting-edge techniques for diagnostics and imaging analysis through graph-based approaches)
Explainability and interpretability of GNNs in healthcare, including advancing methods to ensure transparency and trustworthiness in clinical decision-making.
Scalability and efficiency of graph-based models to address the computational challenges posed by biomedical big data with novel solutions.
Applications in epidemiology and public health, leveraging network science to model the spread of diseases, healthcare resource allocation, and intervention strategies.
Ethical considerations and bias in network-driven biomedical AI (i.e. critical insights on addressing bias and ensuring equitable outcomes in biomedical applications).
INTERDISCIPLINARITY
INTERDISCIPLINARITY
We envision this session as a platform for engaging discussions, interdisciplinary collaborations, and forward-looking perspectives on how Networks and GNNs can drive innovation in bioinformatics and medicine. Whether you are working on these or similar themes, we look forward to your insights.
SPECIAL SESSION PROPOSERS
SPECIAL SESSION PROPOSERS
Barbara Puccio, Magna Græcia University of Catanzaro, Italy.
Annamaria Defilippo, Magna Græcia University of Catanzaro, Italy.
Ugo Lomoio, Magna Græcia University of Catanzaro, Italy.
Pietro Hiram Guzzi, Magna Græcia University of Catanzaro, Italy.
Pierangelo Veltri, University of Calabria, Italy.
Patrizia Vizza, Magna Græcia University of Catanzaro, Italy.
CONTACTS
CONTACTS
ugo.lomoio@unicz.it
hguzzi@unicz.it
pierangelo.veltri@dimes.unical.it
vizzap@unicz.it
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