A Python wrapper for PaDEL-Descriptor software
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Updated
Apr 28, 2025 - Python
A Python wrapper for PaDEL-Descriptor software
💊 Molecular informatics toolkit with integration of bioinformatics and cheminformatics tools for drug discovery
⚗️ An all-in-one solution for chemical property retrieval from PubChem.
python code for calculating the WHALES (Weighted Holistic Atom Localization and Entity Shape) molecular descriptors
Command line and webapp for retrosynthetic disconnections, molecular complexity and synthetic accessibility metrics
A comprehensive tool that automates the extraction of global and local cDFT descriptors using Multiwfn.
The QED (Quantitative Estimation of Drug-likeness) molecular descriptor to use in combination with RDKit
A Molecular Stereostructure Descriptor based on Spherical Projection
A Python wrapper for alvaDesc software
AutoPaDELPy provides an automated user interface for PaDELPy software. It was created to provide a more friendly interaction with the software for the final user.
Repository of the VirtuousUmami tool able to predict the umami taste of a query compound from its molecular structure
Official repository for the paper "Understanding Conformation Importance in Data-driven Property Prediction Models"
SMILE to Descriptors and Fingerprint Generators
Python command line tool for rdkit library, fast, simple and reactive
backup copy of https://code.google.com/archive/p/pychem/downloads
Python wrapper for PaDEL-Descriptor, enabling fast calculation of molecular descriptors and fingerprints from RDKit molecules, with results as pandas DataFrames.
Dataset used in Tox24 challenge
Calculation of peptide molecular descriptors.
👨🔬 A command-line application that utilizes the RDKit library to compute molecular descriptors and fingerprints, aiding in the analysis and characterization of chemical structures
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.
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