emmaking-smith/SET_LSF_CODE
The code corresponding to Predictive Minisci Late Stage Functionalization with Transfer Learning
This project helps chemists and drug discovery scientists predict the most likely reaction sites (regioselectivity) for Minisci Late Stage Functionalization (LSF) on new molecules. You provide an Excel file of candidate molecules, and the system outputs predictions for where the reaction will occur. It's designed for researchers working on drug development and synthetic chemistry.
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Use this if you need to quickly and accurately predict the regioselectivity of Minisci LSF reactions for a set of new chemical compounds in your drug discovery or synthetic chemistry workflow.
Not ideal if your primary need is to predict reactivity for reaction types other than Minisci LSF, or if you require a system that operates outside of a Python environment.
Stars
12
Forks
4
Language
Python
License
MIT
Category
Last pushed
Nov 20, 2024
Commits (30d)
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