| DATE | NOM | INSTITUT | TITRE |
| 16.04.2021 | Sergey Ovchinnikov | Harvard University | A unified framework for understanding and evaluating generative models of protein sequences |
| 16.04.2021 | Jan Skotheim | Stanford University | Towards molecular mechanisms linking cell growth and division |
| 22.04.2021 | Wallace Marshall | UCSF | Pattern formation and regeneration in a single cell |
| 29.04.2021 | Gordon Berman | Emory University | Measuring the hidden dynamics of animal behavior |
| 06.05.2021 | Alexander Rives | Facebook AI research | Biological structure and function emerge from scaling unsupervised learning to 250M protein sequences |
| 07.05.2021 | Matthias Garten | National Institutes of Health | The Malaria Parasite – Red Blood Cell Interface: Installing Transport to Survive in an Organelle-free Host Cell |
| 20.05.2021 | Katharina Ribbeck | MIT | Partners in Slime: How Mucus Regulates Microbial Virulence |
| 03.06.2021 | Richard Neher | University of Basel | Tracking and predicting the evolution of human RNA viruses |
| 17.06.2021 | Nikta Fakhri | MIT Physics | Broken symmetries in living matter |
| 01.07.2021 | Shashi Thutupalli | NCBS | Surfing phage infections during a bacterial range expansion |
| 09.09.2021 | Robert West | EPFL | Shedding light on lives with logs |
| 16.09.2021 | Magnus Rattray | Manchester University | Gaussian process methods for single-cell and spatial transcriptomics |
| 23.09.2021 | Lucy Colwell | Cambridge University – Google | Machine learning for biological sequence design with therapeutic applications |
| 15.10.2021 | Hana El-Samad | UCSF | Build to Understand: the Secret Lives of BioCircuits |
| 28.10.2021 | Marta Luksza | Mount Sinai | Immune selection and predictability of cancer evolution |
| 11.11.2021 | Vahid Shahrezaei | Imperial College London | The cause and consequence of global gene expression scaling with cell size |
| 18.11.2021 | Heinz Köppl | TU Darmstadt | From live cell fluorescence microscopy to moment-based variational inference |
| 25.11.2021 | Edda Klipp | HU Berlin | Understanding a life – integration of time-resolved population and single cell data for a yeast cell from birth to division |