This video represents part 2 in a multi-part video series about the Bioinformatics Project from scratch. In this video I show how to use the dataset from part 1 and use the SMILES notation (which represents the unique chemical structure of compounds) to calculate molecular descriptors. The descriptors we will calculate are Lipinski's descriptors (molecular weight, LogP, number of hydrogen bond donors and number of hydrogen bond acceptors). Finally, we will perform exploratory data analyzes by creating simple box plots and scatter plots to distinguish differences between the active and inactive sets of compounds.

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Summary of Part 1: I showed you how to collect an original dataset in biology that you can use in your Data Science Project. In particular, I demonstrated how to download and preprocess the biological activity data from the ChEMBL database. The dataset consists of compounds (molecules) that have been biologically tested for their activity against the intended target organism/protein.

Code:
Part 1 (concise) Code: https://github.com/dataprofessor/code/blob/master/python/CDD_ML_Part_1_Bioactivity_Data_Concised.ipynb
Part 2 code: https://github.com/dataprofessor/code/blob/master/python/CDD_ML_Part_2_Exploratory_Data_Analysis.ipynb

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Google Colab tips and tricks: https://bit.ly/dataprofessor-google-colab
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Python Data Science Project: https://bit.ly/dataprofessor-python-ds
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