NAMS Tutorials

Here I will provide a series of tutorials for the usage of NAMS.

R based Tutorials


For running the R tutorials, first create a folder in your home directory with these sample data files. Inside that folder, create a subfolder named NAMS where the contents of the all-in-one package should be dropped. [NOTE: if not using Windows, please make sure that a compatible binary has been built for your platform and placed in the same directory of the Python files]

It is recommended that RStudio is used for running the Tutorials, but any R installation should be enough. Some libraries might be required for running the tutorials

The Tutorials

  • NAMS Without Tears - a very simple introduction to running NAMS within R. The bases of molecular similarity and analysis are provided
  • Molecular analysis using NAMS - A more ellaborate tutorial where some elements of topological analysis for exploring the molecular space are given
  • Molecular metric space analysis and inference with NAMS - This tutorial is more complex and the first tutorials should have been followed to grasp the methods used here. In this tutorial NAMS is used as a tool for amalysing and making inference in a potential real world case for in silico drug development. The purpose is to find potential molecular hits for targeting the human Sigma 1 receptor. To run the exercises it is required this dataset containing the SMILES and activity data for 226 molecules retrieved from ChEMBL

These tutorials were made with The R Markdown within RStudio