Morgan Thomas

59 posts

Morgan Thomas

Morgan Thomas

@MorganThomas263

Postdoc at @UPFBarcelona in the compsciencelab working computer-aided drug design, cheminformatics and artificial intelligence

Barcelona Katılım Aralık 2019
159 Takip Edilen276 Takipçiler
Morgan Thomas retweetledi
Gianni De Fabritiis
Gianni De Fabritiis@gdefabritiis·
Preprint release 😀 of "Speak to a Protein," an AI co-scientist that facilitates data gathering and analysis in an interactive collaborative session. It is quite amazing to use. Preprint: arxiv.org/abs/2510.17826
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Austin Tripp
Austin Tripp@austinjtripp·
On Friday I passed my PhD viva with @LucyColwell37 and @cwcoley. Thanks for the great discussion about past and future of machine learning for molecule discovery! 🧪🎓
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Morgan Thomas
Morgan Thomas@MorganThomas263·
Our new library for generative de novo design using PyTorchRL. It is also compatible with MolScore for drug design objectives/benchmarking and PromptSMILES for chemically constrained generation.
Gianni De Fabritiis@gdefabritiis

In #ACEGEN, we take advantage of the #TorchRL library of #PyTorch to do generative chemistry. It implements #REINFORCE, #REINVENT, #A2C, #PPO, #PPOD etc. A solid base for #RL in drug discovery. Code available under MIT. @acellera arxiv.org/abs/2405.04657

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Morgan Thomas
Morgan Thomas@MorganThomas263·
More exciting work to come soon ...
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Morgan Thomas retweetledi
Chris Swain
Chris Swain@macinchem·
Still time to submit abstracts for the 6th AI in Chemistry Symposium rscbmcs.org/events/aichem2…. #AIChem23 #compchem The deadline for oral presentation abstract submission is Midnight (BST), Friday 14th April 2023, poster abstract submission is Midnight (BST), Friday 5th May, 2023.
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Morgan Thomas
Morgan Thomas@MorganThomas263·
5) Although not discussed much in this review due to how recent they are, it'll be interesting to see how diffusion-based models fare in this field - particularly with regards to the type of ligand chemistry generated. Or, how they compare to induced fit docking softwares...
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Morgan Thomas
Morgan Thomas@MorganThomas263·
4) Ultimately, I think the current limiting factor is now fast, accurate binding mode and affinity prediction - either to act as scoring functions in goal-directed learning or to augment limited training datasets for distribution learning.
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