k-ujihara
Synthetic organic chemist. My professional interests are in agrochemicals, vector control.
Takarazuka, Japan
Pinned Repositories
build-rdkit
RDKit .NET wrapper for Windows/Linux.
cdk
The Chemistry Development Kit
ChemFormatter
Chemical formatter for Microsoft Office
ConcatPDF
PDF concatenation tool
NCDK
The Chemistry Development Kit ported to .NET
NCDK-Excel
Add-in for calculating cheminformatics functions on Excel worksheet.
opsin-dotnet
OPSIN - Open Parser for Systematic IUPAC Nomenclature - for .NET Framework
osra_vs
OSRA <https://cactus.nci.nih.gov/osra/> built by Visual Studio
PDFLibNet
k-ujihara's Repositories
k-ujihara/NCDK
The Chemistry Development Kit ported to .NET
k-ujihara/build-rdkit
RDKit .NET wrapper for Windows/Linux.
k-ujihara/NCDK-Excel
Add-in for calculating cheminformatics functions on Excel worksheet.
k-ujihara/opsin-dotnet
OPSIN - Open Parser for Systematic IUPAC Nomenclature - for .NET Framework
k-ujihara/cdk
The Chemistry Development Kit
k-ujihara/AutoDock-GPU
AutoDock for GPUs and other accelerators
k-ujihara/AutoDock-Vina
AutoDock Vina
k-ujihara/azure-docs
Open source documentation of Microsoft Azure
k-ujihara/deep-molecular-optimization
Molecular optimization by capturing chemist’s intuition using the Seq2Seq with attention and the Transformer
k-ujihara/deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
k-ujihara/DeepRMSD-Vina_Optimization
DeepRMSD+Vina is a computational framework that integrates ligand binding pose optimization and screening.
k-ujihara/docs.microsoft.com-nuget.ja-jp
Documentation repo for NuGet localized for ja-jp language-culture
k-ujihara/GraphBP
Official implementation of "Generating 3D Molecules for Target Protein Binding"
k-ujihara/Graphormer
Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material design, drug discovery, etc.
k-ujihara/gruenifai
Implementation grünif.ai: Interactive multi-parameter optimization of molecules in a continuous vector space
k-ujihara/infrag
k-ujihara/Jupyter_Dock
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.
k-ujihara/kmol
kMoL is a machine learning library for drug discovery and life sciences, with federated learning capabilities.
k-ujihara/knime-python
KNIME Python Integration
k-ujihara/materials
Foundation Model for Materials - FM4M
k-ujihara/Meeko
Interfacing RDKit and AutoDock
k-ujihara/molpal
active learning for accelerated high-throughput virtual screening
k-ujihara/moses
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
k-ujihara/mso
Implementation of the method proposed in the paper "Efficient Multi-Objective Molecular Optimization in a Continuous Latent Space" by Robin Winter, Floriane Montanari, Andreas Steffen, Hans Briem, Frank Noé and Djork-Arné Clevert
k-ujihara/oddt
Open Drug Discovery Toolkit
k-ujihara/openmm_runner
k-ujihara/p2rank
P2Rank: Protein-ligand binding site prediction tool based on machine learning. Stand-alone command line program / Java library for predicting ligand binding pockets from protein structure.
k-ujihara/playfield
k-ujihara/rdkit
The official sources for the RDKit library
k-ujihara/ViewSmiles
SMILES/SMARTS/Reaction SMILES viewer