Chemical structure segmentation constitutes a pivotal task in cheminformatics, involving the extraction and abstraction of structural information of chemical compounds from text-based sources, including patents and scientific articles. This study introduces a deep learning approach to chemical struc …

ESM3. Enabling scientists to understand, imagine, and create proteins.

Introduction Every single time I design a protein — using ML or otherwise — I am confident that it is capable of being manufactured. I simply reach o…

Read research published in the Journal of Chemical Information and Modeling Vol. 64 Issue 7 on ACS Publications, a trusted source for peer-reviewed journals.

A visual walkthrough of the AlphaFold3 architecture, with more details and diagrams than you were probably looking for.

I was taken aback by a recent CNBC article entitled “ Generative AI will be designing new drugs all on its own in the near future ”.  I shou...

List of molecular design using Generative AI and Deep Learning - GitHub - AspirinCode/papers-for-molecular-design-using-DL: List of molecular design using Generative AI and Deep Learning

"In the DeepMind paper there are many examples of predicted materials that are clearly nonsensical."

Following up on Part I and Part II, the third post in this series is a collection of review articles published in 2023 that I found helpfu...

I was writing a tokenizer for SMILES and came across a recent paper by the IBM Research team on reaction standardisation which contained a ...

Alchemite™ Analytics accelerates innovation through applied machine learning. Get deep insights into real-world, sparse and noisy, experimental and process data, Reduce the number of experiments required to achieve your goals by 50-80%.

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Seamlessly integrate powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.

GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process. - GT4SD/gt4sd-core: GT4SD, an open-source library to accelerate hypothesis generation in the s...

Contribute to thomas0809/MolScribe development by creating an account on GitHub.

archived 24 Mar 2023 23:53:37 UTC

How to predict protein functions using the CAFA2 Competition Methodology — Part I

University of Basel/ Fall Semester 2022/ Fridays 12:15-14:00 @ Spiegelgasse 5, 05.002

Generative Tensorial Reinforcement Learning (GENTRL) model - insilicomedicine/GENTRL: Generative Tensorial Reinforcement Learning (GENTRL) model

While it's great that we're now seeing papers describing the experimental validation of generative algorithms for molecular design, we need ...

Here’s a roundup of some of the papers I found interesting in 2022. This list is heavily slanted to my interests, which lean toward the appl...

Contribute to bayer-science-for-a-better-life/Img2Mol development by creating an account on GitHub.