MINDPROT: Markov Inside for Drugs and Proteins
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Updated
Mar 18, 2023 - Python
MINDPROT: Markov Inside for Drugs and Proteins
This scripts tries to predict the bioactivity of 131 compounds related to Aspartate Racemase enzyme with the aid of decision trees and SVM
AI-based Quantitative structure Activity relationship study for Alzheimer's disease
A Python package to process & model ChEMBL data.
Drug Discovery for Multiple Sclerosis Disease
HWs - "Computational Drug Design" - Sharif University of Technology (SUT) - Prof. Ali Mohammadian - Fall 2022 (1401-1).
An SGC Chemical Networks Project devoted to the DENV Rdrp, focusing specifically on exploring the ChEMBL database. Please use the link below to view all projects in the READDI-AViDD pipeline.
This ebook has information about life science databases, their SPARQL endpoints, what information they hold, what data models they use, and how to query those.
A Python script predicting pIC50 values of compounds obtained from the ChEMBL database against the target protein, aromatase. The molecular descriptor used in this script is PubChem fingerprint.
Code to retrieve drugs against a desired target using the ChEMBL database API
A Drug Discovery method using CHEMBL database, Lipinski Parameters, molecular fingerprint (padel) for SARS coronavirus 3C-like proteinase.
Drug Discovery model targeting the SARS coronavirus
Supervised classification algorithm to predict if potential drug candidate will inhibit a protein involved in cancer metastasis, achieving 84% accuracy.
Working with ChEMBL Data Web Services to retrieve data.
Machine learning project to evaluate machine learning approaches in drug discovery.
The NeoChemSynthWave: Data project repository.
Automatic extraction of interacting compound-target pairs from ChEMBL.
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