Molecular Modelling and Drug Discovery
By Valence Discovery
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Category: Science
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Episodes: 60
Description
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.
| Episode | Date |
|---|---|
|
Structure-Independent Peptide Binder Design via Generative Language Models | Pranam Chatterjee
|
Jun 20, 2023 |
|
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics | Albert Musaelian
|
Jun 13, 2023 |
|
Multimodal Deep Learning for Protein Engineering | Kevin K. Yang
|
Jun 07, 2023 |
|
Systematic Analysis of Biomolecular Conformational Ensembles with PENSA | Martin Vögele
|
May 30, 2023 |
|
Training Neural Network Potentials: Bayesian and Simulation-based Approaches | Stephan Thaler
|
May 16, 2023 |
|
Accelerating Cryptic Pocket Discovery Using Alphafold and Markov State Modelling | Soumendranath Bhakat
|
May 09, 2023 |
|
Machine Learning Molecules | Gianni De Fabritiis
|
Apr 25, 2023 |
|
Protein Representation Learning by Geometric Structure Pretraining | Zuobai Zhang
|
Apr 19, 2023 |
|
There’s no free lunch, but you can get a discount – applying active learning in drug discovery | Pat Walters & James Thompson
|
Apr 12, 2023 |
|
Cell Morphology-Guided De Novo Hit Design by Conditioning GANs on Phenotypic Image Features | Paula A. Marin Zapata
|
Apr 06, 2023 |
|
Fragment-Based Hit Discovery via Unsupervised Learning of Fragment-Protein Complexes | William McCorkindale
|
Mar 30, 2023 |
|
Calibration and Generalizability of Probabilistic Models on Low-Data Chemical Datasets With DIONYSUS | Gary Tom
|
Mar 22, 2023 |
|
Interpretable Chirality-Aware GNNs for QSAR Modeling in Drug Discovery | Yunchao (Lance) Liu
|
Mar 15, 2023 |
|
Structure-aware Protein Self-supervised Learning | Can Chen
|
Mar 09, 2023 |
|
Differentiable Simulations for Enhanced Sampling of Rare Events | Rafael Gomez-Bombarelli
|
Mar 01, 2023 |
|
Neural Network Potentials for Low-Energy 3D Structure Generation and Reactivity Prediction | Zhen Liu
|
Feb 23, 2023 |
|
Molecule Representation Learning and Discovery: A Perspective from Topology, Geometry, and Textual Description | Shengchao Liu
|
Feb 17, 2023 |
|
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations | Xiang Fu
|
Feb 08, 2023 |
|
Artificial Chemical Intelligence: AI for Chemistry and Chemistry for AI | Pratyush Tiwary
|
Feb 02, 2023 |
|
ProtMD: Incorporating Conformation Flexibility for Drug Binding via Pretraining on Molecular Dynamics Simulations | Fang Wu
|
Jan 26, 2023 |
|
Converging Advances to Accelerate Molecular Simulation | Max Welling
|
Dec 20, 2022 |
|
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking | Hannes Stärk, Gabriele Corso, and Bowen Jing
|
Dec 15, 2022 |
|
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design | Ilia Igashov
|
Nov 29, 2022 |
|
Towards Good Validation Metrics for Generative Models in Offline Model-Based Optimisation
|
Nov 24, 2022 |
|
Predicting Single-Cell Perturbation Responses For Unseen Drugs | Leon Hetzel and Simon Böhm
|
Nov 16, 2022 |
|
Roughness of Molecular Property Landscapes and Its Impact on Modellability | Matteo Aldeghi
|
Nov 09, 2022 |
|
Do Machines Dream of Atoms? Crippen’s logP as a Quantitative Molecular Benchmark for Explainable AI Heatmaps | Jan Jensen
|
Nov 02, 2022 |
|
Now What Sequence? Pre-trained Ensembles for Bayesian Optimization of Protein Sequences | Ziyue Yang
|
Oct 28, 2022 |
|
AlphaFold2, OpenFold, Protein Language Models and Beyond | Nazim Bouatta
|
Oct 19, 2022 |
|
Diffusion probabilistic modelling of protein backbones in 3D for the motif-scaffolding problem | Brian Trippe & Jason Yim
|
Oct 12, 2022 |
|
Geometric Deep Learning for Drug Discovery | Jian Tang
|
Oct 06, 2022 |
|
Kernel Methods for Predicting Yields of Chemical Reactions | Jonathan Hirst
|
Sep 28, 2022 |
|
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization | Tianfan Fu
|
Sep 22, 2022 |
|
Bridging Computation and Experimentation with Evidential Deep Learning | Ava Amini
|
Sep 16, 2022 |
|
Machine Learning for Scientific Discovery | Yoshua Bengio
|
Sep 11, 2022 |
|
Beyond Atoms and Bonds: Contextual Explainability via Molecular Graphical Depictions | Marco Bertolini
|
Jul 14, 2022 |
|
Bayesian Modelling of Synergistic Drug Combination Effects in Cancer Using Gaussian Processes - Leiv Rønneberg
|
Jul 07, 2022 |
|
Open Source Initiatives to Get You Started with AI in Drug Discovery
|
Jun 30, 2022 |
|
Integrating Structure-based and Ligand-based Modeling for Drug Design - Joseph M. Paggi
|
Jun 25, 2022 |
|
Optimal Transport Modeling of Population Dynamics in Single-Cell Biology - Charlotte Bunne
|
Jun 16, 2022 |
|
Data-Efficient Graph Grammar Learning for Molecular Generation - Minghao Guo
|
Jun 02, 2022 |
|
Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Nets - Philipp Seidl
|
May 26, 2022 |
|
Bayesian Optimization for Ternary Complex Prediction - Noah Weber
|
May 22, 2022 |
|
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations - Keir Adams
|
May 11, 2022 |
|
Exposing the Limitations of Molecular Machine Learning with Activity Cliffs - Derek van Tilborg
|
May 05, 2022 |
|
Can Graph Neural Networks Understand Chemistry? - Dominique Beaini
|
Apr 20, 2022 |
|
Epistemic Uncertainty Estimation for Efficient Search of Drug Candidates - Moksh Jain
|
Apr 14, 2022 |
|
RECOVER: Efficient exploration of the drug combination space via model-guided in vitro experiments - Paul Bertin
|
Apr 07, 2022 |
|
Euclidean Deep Learning Models for 3D Structures & Interactions of Molecules - Octavian-Eugen Ganea
|
Mar 31, 2022 |
|
Quantum Machine-Learning for Drug-like Molecules - Clemens Isert
|
Mar 24, 2022 |
|
Structured Refinement Network for Antibody Design - Wengong Jin
|
Mar 17, 2022 |
|
Unbiased De Novo Generation of Organic Molecular Materials - Thomas Cauchy
|
Mar 10, 2022 |
|
Accelerating Organic Synthesis with Chemical Language Models - Philippe Schwaller
|
Mar 02, 2022 |
|
Scalable Geometric Deep Learning on Molecular Graphs - Nathan C. Frey
|
Feb 23, 2022 |
|
Bayesian Optimization over Combinatorial Structures - Aryan Deshwal
|
Feb 16, 2022 |
|
Improving Generalization in Molecular Modelling Through Organization and Augmentation - Huaxiu Yao
|
Feb 10, 2022 |
|
Model Agnostic Generation of Counterfactual Explanations for Molecules - Geemi Wellawatte
|
Feb 02, 2022 |
|
Molecular Synthesizability and Synthetic Tree Generation for Molecular Design - Wenhao Gao
|
Jan 29, 2022 |
|
Challenges of Therapeutics Machine Learning in the Wild - Kexin Huang
|
Jan 22, 2022 |
|
3D Infomax improves GNNs for Molecular Property Prediction - Hannes Stärk
|
Jan 19, 2022 |