Making sense of cells. The role of AI in advancing biomedical and computational biology
Join us at BioLizard to get insights into the practical applications of AI in reshaping data analysis, analyzing single-cell data, deciphering complex biological networks, and advancing our understanding of cellular processes.
Praktische info:
Inschrijven?
- Inschrijvingen: tot 12 jun 2024
- Prijs: Free, but we do ask a no show fee
This event is free for you, but not for us.
Please cancel in advance by sending a mail to info@vaia.be if you cannot make it.
georganiseerd door:
Leertraject
There’s no avoiding the fact that modern biological techniques produce vast amounts of data - orders of magnitude more than just a few decades ago. This abundance of data holds great promise, but also leads to challenges in making sense of, and extracting insights from, the huge number of data points. AI is a powerful tool that can help researchers to address those challenges, and get the most out of their data.
Join us at this event to get insights into the practical applications of AI
in reshaping data analysis, analyzing single-cell data, deciphering complex
biological networks, and advancing our understanding of cellular processes. The
speakers will share real-life use cases to explore the power of AI to advance
biomedical and computational biology, leaving you with new tools to make your
research more data-driven.
Programme
Moderator: Alex Cloherty - BioLizard
16.00 Registration
16.10 Introduction to Flanders AI Research & VAIA - Sabine Demey
16.20 Presentations
- From (explainable) AI model to understanding immune responses
Kris Laukens - Adrem Data Lab, University of Antwerp - Understanding cellular symphonies: from tissue dynamics to new biomarker concepts
Yvan Saeys - Saeys Lab, VIB and Ghent University - Single-cell driven enhancer modelling and design
Stein Aerts - Laboratory of Computational Biology, VIB and KU Leuven - Keeping up with the resolution revolution: AI-driven insights in single cell sequencing
Andrea Del Cortona - BioLizard
17.40 Panel discussion
18.00 Networking reception with appetizers
Van raadsel naar inzicht: hoe verklaarbare AI ons kan helpen biologische complexiteit te ontrafelen
In deze blog van BioLizard verkennen we hoe verklaarbare AI (explainable AI) de besluitvormingsprocessen van AI in computationele biologie kan verhelderen.
From (explainable) AI model to understanding immune responses
Prof. Kris Laukens - Adrem Data Lab, University of Antwerp
Evolutions in sequencing and mass spectrometry technologies are rapidly changing the field of immunology. Immunopeptidomics, single cell sequencing and T cell receptor repertoire sequencing offer unique, rich insights in the complex interactions between the peptide antigen and the components of the adaptive immune system. Unravelling the complexity of this system demands advanced computational solutions that rely heavily on novel AI developments. We will give an introduction to these technical developments of the last few years in the Antwerp AUDACIS consortium, and share experiences how these methods are effectively being used in the elucidation of immune responses in diverse clinical studies. Finally we will show how ImmuneWatch is now transforming these approaches in tools that can improve development processes of smart vaccines, personalised therapies and precision diagnostic applications where T cells play an important role.
Understanding cellular symphonies: from tissue dynamics to new biomarker concepts
Prof. Yvan Saeys - Saeys Lab, VIB and Ghent University
Recent advances in single-cell and spatial omics allow an ever deeper description of cellular phenotypes, but in order to understand biological function we urgently need better models that allow bringing all these parts together and understand how the cells in our biological systems are interacting. In this talk I will describe how cell-cell communication models are revolutionizing our view on modelling tissue spatial organization, and how that leads to a completely novel route of defining novel, potential more targeted biomarkers, using cancer studies as a use case.
Single-cell driven enhancer modelling and design
Prof. Stein Aerts - Laboratory of Computational Biology, VIB and University of Leuven
The combination of scRNA-seq and scATAC-seq allows building gene-regulatory atlases of any tissue and species. I will present several new computational strategies that exploit single-cell multi-omics data: (1) to model genomic enhancers using topic modelling and convolutional neural networks; and (2) to derive “enhancer-GRNs” (eGRN) with key transcription factors, genomic enhancers, and predicted target genes per cell type. I will discuss the results of several case studies where we applied these strategies, including the Drosophila brain, human melanoma, the mouse liver, and the evolution of cell types in the vertebrate telencephalon. Finally, I will discuss how enhancer models based on deep learning can be exploited to design synthetic enhancers for Drosophila and human cell types.
Keeping up with the resolution revolution: AI-driven insights in single cell sequencing
Dr. Andrea Del Cortona - Senior Scientist AI & Analytics, BioLizard
The last decade can be considered a resolution revolution in single cell sequencing, and it is now possible to sequence many different samples in parallel at unprecedented resolution. This provides researchers with new opportunities to test different conditions simultaneously, achieve more robust results, and drive the discovery of improved therapeutics and diagnostics. However, advanced analytical techniques are essential for capturing the complex relationships and patterns within these vast datasets. AI, ML and deep learning methodologies are well positioned to manage the complexity within single cell sequencing datasets, offering a significant promise in revolutionizing early disease detection by identifying patterns and trends in data that may be imperceptible to human analysis alone. Herein, we will present real-life use cases demonstrating how the power of AI combined with the expertise of human experts can transform large sequencing datasets into novel and actionable biomedical insights.
Lesgevers / sprekers
Kris Laukens
Kris Laukens, who acquired his PhD in 2003, is now a Full Professor in bioinformatics at the University of Antwerp's Adrem Data Lab. His research primarily focuses on developing data science and AI methods to turn biomedical data into actionable insights, supporting a range of (pre-)clinical research projects through innovative data analysis and collaboration with hospitals and research institutes. Laukens founded BIOMINA in 2011, a multidisciplinary hub uniting computational research, life sciences, and clinical expertise, now recognized as a core facility of the University of Antwerp. Additionally, he leads the Tech Transfer consortium "Precision Medicine Technologies" (PreMeT), focusing on converting technology into economic and societal value. In 2022, he received the FWO FNRS AstraZeneca Award for his work on human immune response heterogeneity and he has been acknowledged as a top young innovator in Antwerpen. Further, Laukens has founded two successful spin-off companies. In ImmuneWatch BV, he works on AI technology to make T cell repertoire data actionable in clinical applications.
Yvan Saeys
Yvan Saeys obtained his PhD in computer science from Ghent University. After spending time abroad at the University of the Basque Country (Spain) and the University of Lyon (France) he returned to Belgium and established the Data Mining and Modeling for Biomedicine (DAMBI) group at the VIB Center for Inflammation Research (IRC) in Gent. As of 2015, he is a professor at Ghent University and a principal investigator (group leader) at VIB, where he is heading an interdisciplinary research team of 21 people, consisting of mathematicians, computer scientists, engineers and bioinformaticians. The Saeys lab studies the design and application of novel data mining and machine learning techniques for high-dimensional single-cell omics data, including methods to model cell developmental trajectories and intercellular communication. At the methodological level, the lab studies the robustness and interpretability of machine learning models.
Stein Aerts
Prof. Stein Aerts has a multidisciplinary background in both bio-engineering and computer science. During his PhD he was trained in bioinformatics, and during his Postdoc he worked on the genomics of gene regulation in Drosophila. Stein now heads the Laboratory of Computational Biology at the VIB and University of Leuven. His lab focuses on deciphering the genomic regulatory code, using a combination of single-cell, machine-learning, and experimental approaches. His recent scientific contributions include new bioinformatics methods for the analysis of single-cell gene regulatory networks, namely SCENIC and cisTopic; new experimental assays for single-cell ATAC-seq (HyDrop) and for massively parallel enhancer reporter assays; deep learning implementations for enhancer modelling (DeepMEL, DeepFlyBrain, DeepLiver); and methods for AI-driven design of synthetic enhancers for gene therapy. Stein co-founded the Fly Cell Atlas consortium and generated a single-cell atlas of the ageing Drosophila brain. Stein was awarded the 2017 Prize for Bioinformatics and Computational Science from the Biotech Fund and the 2016 Astrazeneca Foundation Award Bioinformatics. He is EMBO member since 2022, obtained an ERC Consolidator Grant in 2016, and an ERC Advanced Grant in 2022. In 2023 Stein founded VIB.AI, the VIB Center for AI and Computational Biology, where he is currently the Scientific Director.
Andrea Del Cortona
Dr. Andrea Del Cortona is a Senior Data Scientist with 9+ years of broad experience spanning both data science and molecular biology. His key skills include bioinformatics, multi-omics data analysis and integration, pipeline engineering, population and comparative genomics, and (single cell-) transcriptomics. At BioLizard, Andrea leverages these skills, alongside his knowledge in data governance and digital transformation, to support biotech and pharma clients in data-driven innovation. Andrea is driven by the goal to positively impact peoples’ lives by providing smart solutions to complex biomedical challenges.
Alex Cloherty
Alex Cloherty is Marketing Manager at BioLizard, an award-winning science communicator, and an enthusiastic speaker and event moderator. She holds a PhD in immunology from the University of Amsterdam, which focused on the role of autophagy in host-virus interactions (HIV-1, DENV-2, and SARS-CoV-2). Alex has published over a hundred articles and short videos that explain biological concepts in jargon-free language on the blog Microbial Mondays, and is active in science communication through leading workshops and moderating live and online events. At BioLizard, Alex is responsible for marketing & communications that support the overarching vision of the company: to improve the quality and longevity of human life around the world by leveraging data better.
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