Molecular Modelling and Drug Discovery

Molecular Modelling and Drug Discovery

Welcome to this space dedicated to the M2D2 Talks co-organized by Valence Discovery and Mila - Quebec AI Institute. From applied research papers to open source projects, we're hoping to use these talks to help demystify AI for drug discovery and make the field more accessible for newcomers. M2D2 will bring our vibrant AI & drug discovery communities together and spark new perspectives, provoke discussions, and offer a safe space to share new ideas. For the best experience, please visit our YouTube channel where slides and video presentations can be referenced.

Den här podcasten är hämtad från ett öppet RSS-flöde och publiceras inte av Podme. Den kan innehålla reklam.

Avsnitt(60)

Predicting Single-Cell Perturbation Responses For Unseen Drugs | Leon Hetzel and Simon Böhm

Predicting Single-Cell Perturbation Responses For Unseen Drugs | Leon Hetzel and Simon Böhm

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

16 Nov 202258min

Roughness of Molecular Property Landscapes and Its Impact on Modellability | Matteo Aldeghi

Roughness of Molecular Property Landscapes and Its Impact on Modellability | Matteo Aldeghi

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

9 Nov 20221h 6min

Do Machines Dream of Atoms? Crippen’s logP as a Quantitative Molecular Benchmark for Explainable AI Heatmaps | Jan Jensen

Do Machines Dream of Atoms? Crippen’s logP as a Quantitative Molecular Benchmark for Explainable AI Heatmaps | Jan Jensen

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

2 Nov 202253min

Now What Sequence? Pre-trained Ensembles for Bayesian Optimization of Protein Sequences | Ziyue Yang

Now What Sequence? Pre-trained Ensembles for Bayesian Optimization of Protein Sequences | Ziyue Yang

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

28 Okt 202249min

 AlphaFold2, OpenFold, Protein Language Models and Beyond | Nazim Bouatta

AlphaFold2, OpenFold, Protein Language Models and Beyond | Nazim Bouatta

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

19 Okt 20221h 1min

Diffusion probabilistic modelling of protein backbones in 3D for the motif-scaffolding problem | Brian Trippe & Jason Yim

Diffusion probabilistic modelling of protein backbones in 3D for the motif-scaffolding problem | Brian Trippe & Jason Yim

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

12 Okt 20221h 2min

Geometric Deep Learning for Drug Discovery | Jian Tang

Geometric Deep Learning for Drug Discovery | Jian Tang

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

6 Okt 20221h 3min

Kernel Methods for Predicting Yields of Chemical Reactions | Jonathan Hirst

Kernel Methods for Predicting Yields of Chemical Reactions | Jonathan Hirst

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides. If you enjoyed this talk, consider joining the Molecular Modeling and D...

28 Sep 202250min

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