An R script that uses MACCS166 chemical fingerprint and calculates Jaccard Index/Tanimoto Coefficient for a list of Aspartate Racemase Ligands
-
Updated
Feb 1, 2022 - R
An R script that uses MACCS166 chemical fingerprint and calculates Jaccard Index/Tanimoto Coefficient for a list of Aspartate Racemase Ligands
A proof-of-concept type demo of the Binary Encoded SMARTS Pattern Enumeration + Molecular aCCess System molecular descriptor developed as part of Bachelor's Thesis: "Molecular descriptor engineering for machine learning predictions in atmospheric science." Includes a toy data set for demonstrative purposes.
This project trains a Morgan Fingerprint model to predict lipophilicity.
This scripts tries to predict the bioactivity of 131 compounds related to Aspartate Racemase enzyme with the aid of decision trees and SVM
Automatic QSAR workflow for Python
Add a description, image, and links to the maccs-fingerprint topic page so that developers can more easily learn about it.
To associate your repository with the maccs-fingerprint topic, visit your repo's landing page and select "manage topics."