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.

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Jaksot(60)

There’s no free lunch, but you can get a discount – applying active learning in drug discovery | Pat Walters & James Thompson

There’s no free lunch, but you can get a discount – applying active learning in drug discovery | Pat Walters & James Thompson

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠YouTube channel ⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies molecula...

12 Huhti 202352min

Cell Morphology-Guided De Novo Hit Design by Conditioning GANs on Phenotypic Image Features | Paula A. Marin Zapata

Cell Morphology-Guided De Novo Hit Design by Conditioning GANs on Phenotypic Image Features | Paula A. Marin Zapata

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠YouTube channel ⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies molecula...

6 Huhti 202349min

Fragment-Based Hit Discovery via Unsupervised Learning of Fragment-Protein Complexes | William McCorkindale

Fragment-Based Hit Discovery via Unsupervised Learning of Fragment-Protein Complexes | William McCorkindale

[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...

30 Maalis 202353min

Calibration and Generalizability of Probabilistic Models on Low-Data Chemical Datasets With DIONYSUS | Gary Tom

Calibration and Generalizability of Probabilistic Models on Low-Data Chemical Datasets With DIONYSUS | Gary Tom

[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 an...

22 Maalis 202352min

Interpretable Chirality-Aware GNNs for QSAR Modeling in Drug Discovery | Yunchao (Lance) Liu

Interpretable Chirality-Aware GNNs for QSAR Modeling in Drug Discovery | Yunchao (Lance) Liu

[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...

15 Maalis 202349min

Structure-aware Protein Self-supervised Learning | Can Chen

Structure-aware Protein Self-supervised Learning | Can Chen

[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 Maalis 202330min

Differentiable Simulations for Enhanced Sampling of Rare Events | Rafael Gomez-Bombarelli

Differentiable Simulations for Enhanced Sampling of Rare Events | Rafael Gomez-Bombarelli

[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...

1 Maalis 20231h 1min

Neural Network Potentials for Low-Energy 3D Structure Generation and Reactivity Prediction | Zhen Liu

Neural Network Potentials for Low-Energy 3D Structure Generation and Reactivity Prediction | Zhen Liu

[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...

23 Helmi 202349min

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