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... something totally new.
Catalyst is compatible with Python 3.6+. PyTorch 1.1+, and has been tested on Ubuntu 16.04/18.04/20.04, macOS 10.15, Windows 10 and Windows Subsystem for Linux. It's part of the PyTorch Ecosystem, as well as the Catalyst Ecosystem which includes Alchemy (experiments logging & visualization) and Reaction (convenient deep learning models serving).
Predicting Organic Reactions using Neural Networks.
The intend is to solve the forward-reaction prediction problem, where the reactants are known and the interest is in generating the reaction products using Deep learning. This Graphical User Interface takes simplified molecular-input line-entry system (SMILES) as an input and generates the product SMILE & molecule.
Beam search is used in Version 2, to generate top 5 predictions.
Maximum input length for the model is 15 (excluding spaces).
An application create, simulate and adjust N-linked glycosylation.
... is used to adjust the kinetic parameters of Michaelis-Menten equations in glycosylation reaction network. A dynamic plot is supplied to show the value of mole amout and mole fraction of various glycoform.
Thanks to Alexey Balakin and Alessandro Presta. Alexey Balakin supply mathgl(https://sourceforge.net/projects/mathgl) that make the implementation of dynamic plot in this application easily. Alessandro Presta supply fga(https://sourceforge.net/projects/fga) that provide a powerful use of GA.