The availability of genomic data has grown exponentially in the last decade, mainly due to the development of new sequencing technologies.
Formal XAI (explainable AI) is a growing area that focuses on computing explanations with mathematical guarantees for the decisions made by ML models.
Gene annotation addresses the problem of predicting unknown associations between gene and functions (e. g., biological processes) of a specific organism.
Node classification is the task of inferring or predicting missing node attributes from information available for other nodes in a network.
The spectral evolution model aims to characterize the growth of large networks (i. e., how they evolve as new edges are established) in terms of the eigenvalue decomposition of the adjacency matrices.
The growing use of Machine Learning has produced significant advances in many fields.