Artificial Intelligence in the Era of Omics: Challenges and Perspectives for Bioinformatics
Artificial Intelligence in the Era of Omics: Challenges and Perspectives for Bioinformatics
School or Professorship:
The rapid expansion of high-throughput omics technologies has transformed the field of Bioinformatics, generating vast, multi-layered datasets that capture biological systems at unprecedented resolution. In this context, artificial intelligence (AI) has emerged as a powerful framework for extracting meaningful patterns from high-dimensional data, enabling advances in disease prediction, biomarker discovery, precision medicine, and drug development.
However, the integration of AI into omics research is not free from challenges. These include the high dimensionality of the data, costs in data generation, batch effects and biological variability, and the trade-off between predictive performance and interpretability that result in poor model generalizability. Moreover, ethical concerns, data privacy, and biases in genomic datasets further complicate clinical deployment.
This talk will explore both the opportunities and the limitations of AI in the era of omics, highlighting emerging directions as well as the methodological, technical, and ethical challenges currently shaping the implementation of AI in bioinformatics.
Speaker:
Francesco Gualdi is a Postdoctoral Researcher at the Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA) in Lugano, Switzerland. He obtained his PhD in Biomedicine in 2024 from Universitat Pompeu Fabra in Barcelona, where he was part of the Integrative Biomedical Informatics Group within the Research Programme on Biomedical Informatics.
He earned his Bachelor of Science in Biology from the University of Ferrara in 2017, focusing on the characterization of cells derived from the intervertebral disc. In 2020, he completed his Master of Science at the University of Verona in the Structural Biology group, with a thesis dedicated to developing a curated database of human GPCR structures.
His research focuses on uncovering the molecular basis of complex diseases through the integrative analysis of multi-omics data. He develops bioinformatics frameworks that combine network-based methodologies with artificial intelligence techniques to identify and prioritize biomarkers potentially implicated in human disorders.
Program
4.00 pm – 4.05 pm: Opening & Introduction
4.05 pm – 4.50 pm: Talk
4.50 pm – 5.05 pm: Q&A
5.05 pm – 5.45 pm: Apéro
However, the integration of AI into omics research is not free from challenges. These include the high dimensionality of the data, costs in data generation, batch effects and biological variability, and the trade-off between predictive performance and interpretability that result in poor model generalizability. Moreover, ethical concerns, data privacy, and biases in genomic datasets further complicate clinical deployment.
This talk will explore both the opportunities and the limitations of AI in the era of omics, highlighting emerging directions as well as the methodological, technical, and ethical challenges currently shaping the implementation of AI in bioinformatics.
Speaker:
Francesco Gualdi is a Postdoctoral Researcher at the Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA) in Lugano, Switzerland. He obtained his PhD in Biomedicine in 2024 from Universitat Pompeu Fabra in Barcelona, where he was part of the Integrative Biomedical Informatics Group within the Research Programme on Biomedical Informatics.
He earned his Bachelor of Science in Biology from the University of Ferrara in 2017, focusing on the characterization of cells derived from the intervertebral disc. In 2020, he completed his Master of Science at the University of Verona in the Structural Biology group, with a thesis dedicated to developing a curated database of human GPCR structures.
His research focuses on uncovering the molecular basis of complex diseases through the integrative analysis of multi-omics data. He develops bioinformatics frameworks that combine network-based methodologies with artificial intelligence techniques to identify and prioritize biomarkers potentially implicated in human disorders.
Program
4.00 pm – 4.05 pm: Opening & Introduction
4.05 pm – 4.50 pm: Talk
4.50 pm – 5.05 pm: Q&A
5.05 pm – 5.45 pm: Apéro