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  • 👋 Hi, I’m @Jianmin Wang(王建民)
  • 👀 I’m interested in drug discovery and development, data science, artificial intelligence, etc.
  • 🌱 I’m currently learning ...
  • 💞️ I’m looking to collaborate on ...
  • 📫 E-mail: [email protected] DrugAI

Jianmin Wang's Projects

qmdesc icon qmdesc

A graph neural network based QM descriptor predictor

qmpy icon qmpy

A suite of computational materials science tools.

qsar icon qsar

Neural Network based model relevant for drug discovery

qsar-drugdiscovery-with-rdkit icon qsar-drugdiscovery-with-rdkit

ChEMBL Database used to create Lipinski Descriptors (ADME Pharmokinetic Profile) to use in a Random Forest Regression Model

qsar-tools icon qsar-tools

Scripts for assisting in modeling quantitative structure activity relationships from 2D chemical data

qsar-tutorial icon qsar-tutorial

QSAR Tutorial - Obtaining data from ChEMBL and playing around with RDKit

quantum-machine-learning icon quantum-machine-learning

Quantum Machine Learning, Quantum Approximation Optimization Algorithms, VQE, Quantum Chemistry, PennyLane and Qiskit

quax icon quax

Arbitrary-order derivatives of popular electronic structure methods, such as Hartree-Fock and coupled cluster theory.

qubekit icon qubekit

Quantum Mechanical Bespoke Force Field Derivation Toolkit

qvina icon qvina

Accurately speed up AutoDock Vina

r-bert icon r-bert

Pytorch implementation of R-BERT: "Enriching Pre-trained Language Model with Entity Information for Relation Classification"

ramanet icon ramanet

Preforms De novo protein design using machine learning and PyRosetta to generate a novel protein structure

rascore icon rascore

Retrosynthetic Accessibility (RA) score learned from computer aided synthesis planning

rcpi icon rcpi

Molecular informatics toolkit with a comprehensive integration of bioinformatics and cheminformatics tools for drug discovery.

rdeditor icon rdeditor

Simple RDKit molecule editor GUI using PySide

rdkit icon rdkit

The official sources for the RDKit library

rdkittutorial icon rdkittutorial

Tutorial on the usage of Rdkit, Pandas, sklearn, machine learning, descriptor calculation, etc.. in the context of bioactivity predictive modeling

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