The talks featured in this room on the FEBS Network are recordings of live presentations from invited speakers at the EMBO|FEBS Lecture Course ‘Cancer systems biology: Promises of artificial intelligence’, held as a virtual event from September 28 to October 2, 2020.

This 3rd Course on Computational Systems Biology of Cancer was organized by the Institut Curie Training Unit, with support from EMBO and FEBS.

The programme below has links to the recordings of the event talks in this room. You can also read more about the course objectives, history and environment and get an overview of the event, including some great photos, on the Institut Curie website here.

EMBO|FEBS Lecture Course ‘Cancer systems biology: Promises of artificial intelligence’, September 28 – October 2, 2020

September 28, 2020 Session 1: Machine learning in prior knowledge applications for data analysis

Chair: Emmanuel Barillot

Talk 1: Andrei Zinovyev, Institut Curie, France. Didactic introductory lecture on AI approaches in systems biology

September 28, 2020 Session 2: Network biology in Artificial Intelligence era

Chair: Laurence Calzone

Talk 2: Laura Cantini, IBENS-ENS, France. Benchmarking of computational approaches to multi-omics data analysis

Talk 3: Nataša Pržulj, Barcelona Supercomputing Center, Spain. Analyzing Network Data in Biology and Medicine

September 29, 2020 Session 3: Patient stratification and disease classification using Artificial Intelligence methods (1)

Chair: Inna Kuperstein

Talk 4: Nataliya Sokolovska, University Pierre et Marie Curie, France. Interpretable models for clinical scores

Talk 5: David Wedge, The Big Data Institute, UK. Stratification of prostate cancers through the application of machine learning to sequencing data

September 29, 2020 Session 4: Patient stratification and disease classification using Artificial Intelligence methods (2)

Chair: Inna Kuperstin

Talk 6: Susana Vinga, Instituto Superior Técnico, Portugal. Cancer classification and survival analysis through sparse optimization and network-based regularisers

Talk 7: Valentina Boeva, ETH, Zurich, Switzerland. Machine learning methods for the detection of intratumoral heterogeneity in cancer

September 30, 2020 Session 5: Machine Learning applications in precision medicine (1)

Chair: Chloé-Agathe Azencott

Talk 8: Chloé-Agathe Azencott, Centre for Computational Biology, MINES ParisTech, France. Feature selection with regularization in high-dimensional genomics data

Talk 9: Yves Moreau, KU Leuven, Belgium. Bayesian matrix factorization and deep learning for drug discovery and precision medicine

September 30, 2020 Session 6: Machine Learning applications in precision medicine (2)

Chair: Chloé-Agathe Azencott

Talk 10: Jean-Philippe Vert, Google, France. Robust machine learning for cancer precision medicine

Talk 11: Olli Kallioniemi, SciLifeLab, Sweden. AI approaches in Precision Cancer Medicine

Talk 12: Lodewyk Wessels, Netherlands Cancer Institute, The Netherlands. Mapping cellular networks in cancer

October 1, 2020 Session 7: Tumor genetics and epigenetics (1)

Chair: Emmanuel Barillot

Talk 13: Andrew Teschendorff, University College London, UK. Machine Learning approaches for large scale multi-dimensional cancer omics data analysis

Talk 14 (part 1): Julio Saez-Rodriguez, Heidelberg University, Germany. Supporting Machine Learning with Prior Biological Knowledge to extract insight from omics data

Talk 14 (part 2): Julio Saez-Rodriguez, Heidelberg University, Germany. Supporting Machine Learning with Prior Biological Knowledge to extract insight from omics data

Talk 15: Christina Leslie, Memorial Sloan Kettering Cancer Center, USA. Machine learning in regulatory genomics and systems biology

October 1, 2020 Session 8: Tumor genetics and epigenetics (2)

Chair: Laurence Calzone

Talk 16: Touati Benoukraf, Memorial University of Newfoundland, Canada. DNA methylation and Cancer

October 1, 2020 Special session: Career development workshop

Chair: Laurence Calzone

Career Development Talk 1: Ana Rita Furtado, Institut Curie, France. What skills are you expected to develop during your research training?

Career Development Talk 2: Emmanuel Barillot, Institut Curie, France. Career in a Bioinformatics core facility

Career Development Talk 3: Maria Papatriantafyllou, FEBS, UK. Career paths

October 2, 2020 Session 9: Bioimage Informatics in cancer research (1)

Chair: Thomas Walter

Talk Not Available: Nasir Rajpoot, University of Warwick, UK. The Promise of Computational Pathology

Talk 18: Florian Markowetz, University of Cambridge, UK. Image analysis of the tumour tissue and early detection by AI

October 2, 2020 Session 10: Bioimage Informatics in cancer research (2)

Chair Thomas Walter

Talk 19: Thomas Walter, Centre for Computational Biology, MINES ParisTech, France. Exploring the spatial aspects of gene expression

Talk 20: Emma Lundberg, SciLifeLab, Sweden. AI for improved spatial proteomics