Pinned Repositories
ATOMRefine
3D equivariant graph transformer for all-atom refinement of protein tertiary structures
bio-diffusion
A geometry-complete diffusion generative model (GCDM) for 3D molecule generation and optimization
cryo2struct
The programs for preprocessing cryo-EM density maps for machine learning
cryoppp
The programs of creating cryo-EM particle picking datasets
CryoVirusDB
A dataset of labeled virus particles in cryo-EM micrographs (images) for training and testing machine learning methods of virus particle picking
DeepInteract
A geometric deep learning pipeline for predicting protein interface contacts. (ICLR 2022)
DIPS-Plus
The Enhanced Database of Interacting Protein Structures for Interface Prediction
GCPNet
A PyTorch implementation of Geometry-Complete SE(3)-Equivariant Perceptron Networks (GCPNets)
MULTICOM3
The software system of improving AlphaFold2- and AlphaFold-Multimer-based protein tertiary & quaternary structure prediction. It was developed by the Bioinformatics and Machine Learning Lab at the University of Missouri. It was blindly tested in CASP15 and ranked among the best server predictors in 2022. It improves AlphaFold's accuracy by 5-10%.
PoseBench
Comprehensive benchmarking of protein-ligand structure generation methods
BioinfoMachineLearning's Repositories
BioinfoMachineLearning/bio-diffusion
A geometry-complete diffusion generative model (GCDM) for 3D molecule generation and optimization
BioinfoMachineLearning/cryoppp
The programs of creating cryo-EM particle picking datasets
BioinfoMachineLearning/PoseBench
Comprehensive benchmarking of protein-ligand structure generation methods
BioinfoMachineLearning/DIPS-Plus
The Enhanced Database of Interacting Protein Structures for Interface Prediction
BioinfoMachineLearning/GCPNet
A PyTorch implementation of Geometry-Complete SE(3)-Equivariant Perceptron Networks (GCPNets)
BioinfoMachineLearning/CryoVirusDB
A dataset of labeled virus particles in cryo-EM micrographs (images) for training and testing machine learning methods of virus particle picking
BioinfoMachineLearning/ATOMRefine
3D equivariant graph transformer for all-atom refinement of protein tertiary structures
BioinfoMachineLearning/MULTICOM3
The software system of improving AlphaFold2- and AlphaFold-Multimer-based protein tertiary & quaternary structure prediction. It was developed by the Bioinformatics and Machine Learning Lab at the University of Missouri. It was blindly tested in CASP15 and ranked among the best server predictors in 2022. It improves AlphaFold's accuracy by 5-10%.
BioinfoMachineLearning/cryo2struct
The programs for preprocessing cryo-EM density maps for machine learning
BioinfoMachineLearning/EnQA
A 3D-equivariant neural network for protein structure accuracy estimation
BioinfoMachineLearning/DeepRefine
A geometric deep learning method for refining and assessing protein complex structures.
BioinfoMachineLearning/CDPred
Deep transformer for predicting interchain residue-residue distances of protein complexes
BioinfoMachineLearning/DProQ
Deep learning prediction of protein complex structure quality
BioinfoMachineLearning/GCPNet-EMA
Protein Structure Accuracy Estimation using Geometry-Complete Perceptron Networks (Protein Science 2024)
BioinfoMachineLearning/TransFew
Transformer for protein function prediction (version 2)
BioinfoMachineLearning/MULTICOM_qa
Evaluate the quality of protein multimer structure models
BioinfoMachineLearning/ScHiCEDRN
Single cell 3D genome modeling tools developed in the Bioinformatics and Machine Learning Lab
BioinfoMachineLearning/hicdiff
Diffusion models for denoising Hi-C chromosome conformation capturing data
BioinfoMachineLearning/SERSFormer
Transformers for predicting food contamination
BioinfoMachineLearning/BML_HiC_Data_Analysis
A set of tools for Hi-C data analysis developed by Bioinformatics and Machine Learning Lab
BioinfoMachineLearning/DeepCryoPicker
This is the python implementation of the original DeepCryoPicker for picking single protein particles in cryo-EM images.
BioinfoMachineLearning/FunBench
The programs and data for benchmarking protein function site prediction methods
BioinfoMachineLearning/GCDM-SBDD
A geometry-complete diffusion generative model (GCDM) for structure-based drug design
BioinfoMachineLearning/GD-multimer
Stochastic gradient descent method for reconstructing protein multimer structures from inter-chain contacts/distances
BioinfoMachineLearning/dagmsa
DAGMSA: Direct Acyclic Graph-based Multiple Sequence Alignments (MSA) for Protein Multimer Structure Prediction
BioinfoMachineLearning/DiffDock
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
BioinfoMachineLearning/JCVIDB
A data repository for JCVI minimum cells
BioinfoMachineLearning/openfold-bugfixes
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
BioinfoMachineLearning/TransPro
1D transformer for predicting protein structural features (secondary structure, solvent accessibility)
BioinfoMachineLearning/tulip
Template-based modeling for accurate prediction of ligand-protein complex structures (TULIP)