Kihara Protein Bioinformatics Laboratory
Software developed in the Kihara Lab
Purdue University, IN, USA
Pinned Repositories
ACC-UNet
ACC-UNet is A Completely Convolutional UNet model inspired from transformer-based UNets
CryoREAD
CryoREAD: a computational tool using deep learning to automatically build full DNA/RNA atomic structure from cryo-EM map.
DAQ
DAQ: Residue-Wise Local Quality Estimation for Protein Models from Cryo-EM Maps
DiffModeler
DiffModeler: a diffusion model based protein complex structure modeling tool.
Distance-AF
Public version for Distance-AF
DOVE
A Deep-learning based dOcking decoy eValuation mEthod
Emap2sec
Emap2sec is a computational tool to identify protein secondary structures
Emap2secPlus
Emap2sec+: Detecting Protein and DNA/RNA Structures in Cryo-EM Maps of Intermediate Resolution Using Deep Learning
GNN_DOVE
Code for "Protein Docking Model Evaluation by Graph Neural Networks"
GO2Sum
GO2Sum is a deep learning based summarizer that generates human-readable summaries for GO term annotations made by protein function prediction methods.
Kihara Protein Bioinformatics Laboratory's Repositories
kiharalab/ACC-UNet
ACC-UNet is A Completely Convolutional UNet model inspired from transformer-based UNets
kiharalab/GNN_DOVE
Code for "Protein Docking Model Evaluation by Graph Neural Networks"
kiharalab/DOVE
A Deep-learning based dOcking decoy eValuation mEthod
kiharalab/CryoREAD
CryoREAD: a computational tool using deep learning to automatically build full DNA/RNA atomic structure from cryo-EM map.
kiharalab/DiffModeler
DiffModeler: a diffusion model based protein complex structure modeling tool.
kiharalab/Distance-AF
Public version for Distance-AF
kiharalab/Emap2sec
Emap2sec is a computational tool to identify protein secondary structures
kiharalab/Emap2secPlus
Emap2sec+: Detecting Protein and DNA/RNA Structures in Cryo-EM Maps of Intermediate Resolution Using Deep Learning
kiharalab/DAQ
DAQ: Residue-Wise Local Quality Estimation for Protein Models from Cryo-EM Maps
kiharalab/EM-GAN
EM-GAN is a computational tool, which enables capturing protein structure information from cryo-EM maps more effectively than raw maps. It is based on 3D deep learning. It is aimed to help protein structure modeling from cryo-EM maps.
kiharalab/GO2Sum
GO2Sum is a deep learning based summarizer that generates human-readable summaries for GO term annotations made by protein function prediction methods.
kiharalab/RL-MLZerD
kiharalab/Flex-LZerD
kiharalab/VESPER
kiharalab/DeepMainMast
DeepMainmast
kiharalab/Domain-PFP
Domain-PFP is a self-supervised method to predict protein functions from the domains
kiharalab/DAQ-Refine
kiharalab/AFM-RL
kiharalab/DistPepFold
Public version for DistPepFold
kiharalab/OC_Finder
kiharalab/contactPFP
Protein function prediction based on predicted residue-residue contacts
kiharalab/NuFold
NuFold: End-to-End Approach for RNA Tertiary Structure Prediction with Flexible Nucleobase Center Representation
kiharalab/Attention_AD
Attention LSTM code for "Activation of gene expression by nucleosome detergents"
kiharalab/ComplexModeler
kiharalab/MAINMASTseg
Automated Segmentation Program for EM map with symmetry
kiharalab/AF2_Distaf
Embedding generation for Distance-AF using full MSA
kiharalab/ColabFold
Making Protein folding accessible to all!
kiharalab/ColabFold_Distaf
Embedding generation for Distance-AF
kiharalab/ColabFoldDAQ
Making Protein folding accessible to all!
kiharalab/GNN-TAD