Jianmin Wang

papers-for-molecular-design-using-DL. List of Molecular and Material design using Generative AI and Deep Learning

awesome-AI4MolConformation-MD. List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

awesome-BioMolGenFold. RNA, mRNA, DNA, Peptide, Protein, Antibody and Complex | Folding

AlphaPPImd. Exploring the conformational ensembles of protein-protein complexes with transformer-based generative neural networks

iPPIGAN. De novo molecular design with deep molecular generative models for protein-protein interaction(PPI) inhibitors

GENiPPI. Interface-aware molecular generative framework for protein-protein interaction modulators

DiffIUPAC. Diffusion-based generative drug-like molecular editing with chemical natural language

awesome-ChemicalSpectraAI. AI for Chemical Spectra

protein-science. A collection of useful tutorials for Protein Science

TransAntivirus. Transformer-based molecular generative model for antiviral drug design

DrugAI_Drug-Likeness. Drug-Likeness

iupacGPT. IUPAC-based large-scale molecular pre-trained model for property prediction and molecular generation

AMPTrans-lstm. Application of deep generative model discovers novel and diverse functional peptides against microbial resistance

QRCI. A Quantitative Ring Complexity Index for Profiling Ring Topology and Chemical Diversity

awesome-cheminformatics. A curated list of awesome Cheminformatics libraries and software.

MD-analysis-tools-scripts. Tools and scripts for analyses of molecular dynamics simulations

BigData_AI_DrugDiscovery. A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks.

drug-likeness_space. Explore drug-like space with deep generative models

Bioinformatics-with-R-cookbook. Learn some basic applications of bioinformatics in R.

AI4Chemistry-Zoo.

nlp. Datasets and evaluation metrics for Natural Language Processing in NumPy, Pandas, PyTorch and TensorFlow

compchem_skills. Computational Chemistry Tutorials

StackPPI. Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier

papers_for_protein_design_using_DL. List of papers about Proteins Design using Deep Learning

Gromacs-notebook.

Dynamics-PLI. Molecular dynamics-powered hierarchical geometric deep learning framework for protein-ligand interaction

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials. A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

LGBM-DTIs. LGBM-DTIs: Predicting drug-target interactions using LightGBM with protein multi-information and molecular structure

Drug3D-Net. A Spatial-temporal Gated Attention Module for Molecular Property Prediction Based on Molecular Geometry

patent-clinical-candidate-characteristics. Source code and data repository for paper titled "Exploring SureChEMBL from a drug discovery perspective".

jupyter-genomics. A collection of Jupyter notebooks authored by the UCSD Center for Computational Biology & Bioinformatics (http://compbio.ucsd.edu). These include methods on utilizing cloud computing resources and analysis of data from next-generation sequencing, systems biology, and microbiome.

LLM4Mol. A comprehensive repository dedicated to the collection and exploration of studies utilizing Large Language Models for molecular design, protein research, and material science.

MetabolicPathwayPrediction. Jupyter Notebook

AlphaPPIMI. AlphaPPIMI: A Comprehensive Deep Learning Framework for Predicting PPI-Modulator Interactions

DNN-DTIs. DNN-DTIs: improved drug-target interactions prediction using XGBoost feature selection and deep neural network

MultiPPIMI. a deep learning framework for predicting interactions between protein-protein interaction targets and modulators

TargetGAN. Deep generative model for drug design from protein target sequence

DockingGA. Python

amber_tutorials. Some tutorials on how to use AMBER simulation package. Especially for Amber22+AmberTools23.

QEPPI-community. Community-Maintained Version of mordred (Quantitative Estimate Index for Early-Stage Screening of Compounds Targeting Protein-Protein Interactions)

Structural-Bioinformatics. This repository includes the slides and the practicals for the course of Structural Bioinformatics of the MBB/QB degrees at the University of Milano, originally inspired by https://github.com/pb3lab/ibm3202

PyMOLfold. Plugin for folding sequences directly in PyMOL

Neural-Network-Models-for-Chemistry. A collection of Nerual Network Models for chemistry

LLAPA. source code of Large Language and Protein Assistant for Protein-Protein Interactions Prediction

AspirinCode. Config files for my GitHub profile.

molecular-entropies. Data and analysis scripts for understanding molecular entropies, including conformer flexibility

DL4MolecularGraph. Literature of deep learning for graphs in Chemistry and Biology

reinvent-dnc. Differentiable Neural Computer (DNC) implemented onto REINVENT (tool for molecular generation in de novo drug discovery)

Introduction-to-Applied-Mathematics-And-Informatics-In-Drug-Discovery. Applied Mathematics and Informatics in Drug Discovery (AMIDD) course

awesome_for_material_discovery_using_DL.

DeepPocket. Ligand Binding Site detection using Deep Learning

NMR-TS. Molecule identifier from NMR spectrum using de novo molecule generator

gmx_MMPBSA. gmx_MMPBSA is a new tool aid to perform end-state free energy calculations based on AMBER's MMPBSA.py with GROMACS files.