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GNN, GCN, Molecular Solubility, RDKit, Cheminformatics
With the rise of deep learning models and the successful result showing in different domains (such as Computer vision and Natural language processing)researchers and laboratories of chem-informatics try to apply these techniques in drug design and discovery. recently,the application of Deep Learning in this area of research has made a good progress but it is in the early stage and we can’t say that the results lead us to rational drug design,which mean designing new drugs without in Vivo and human trials. in this project project, we apply different machine learning models on drug design and discovery datasets with multiple tasks (each dateset has a task or goal to achieve from the analysis) after the evaluation and comparison of our results and the benchmarks we found that the huge problem is the small amount of data.
Molecule water solubility prediction using DeepChem.
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Using DeepChem with TensorFlow 2.x and Keras
HIV molecules classification using GNN with attention
some scripts using deepchem
This is an introductory deep learning model which uses the Deepchem package. Lots of credit has to be given to the authors(Ramsundar B., Eastman P., Walters P., Pande V.) of the book "Deep Learning for the Life Sciences". This book has been a gold mine in terms of my exploration and journey in DeepLearning in the field of biochemistry.
Docker for reproducing solubility model
This is a research project as part of the course CSE-700 : Independent Study, that I had taken up for Spring 2020 at the University at Buffalo.
Scripts that discussed in the book chapter titled "Toxicity Forecaster: Navigating Data-Driven AI/ML Models - From Theory to Practice"