A set of libraries for aligning, profiling, and predicting the structure of proteins
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Updated
Nov 1, 2017 - Python
A set of libraries for aligning, profiling, and predicting the structure of proteins
A deep learning method that identifies improved protein conformational states in trajectory data from refinement simulations
spdkit: Structure Predication Development Kit
Recurrent neural network implementations for protein secondary structure prediction and language models
Active Imitation Learing with Noisy Guidance
Computing descriptors for AIRSS style SHELX files.
An implementation of a genetic algorithm in Python for predicting equilibrium crystal structures for a given potential. The potential implemented here is the Daoud-Cotton model, but this can be easily changed.
An implementation of the DeepMind's AlphaFold based on PyTorch for research
Data and code for the manuscript "Assessing the utility of CASP14 models for Molecular Replacement: https://doi.org/10.22541/au.162412334.48194370/v1
Deep neural models for core NLP tasks (Pytorch version)
Official code repository for EquiFold: Protein Structure Prediction with a Novel Coarse-Grained Structure Representation
spdkit: Structure Predication Development Kit
[ACL'23 main] DICE: Data-Efficient Clinical Event Extraction with Generative Models
[EMNLP 2022] Generative Knowledge Graph Construction: A Review
Protein Secondary Structure predictor using Convolutional Neural Networks
Searching proteins against a database of embeddings
[ACL 2023] SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres
A pipeline for AlphaFold2-Multimer on a SLURM compute cluster with visualization in ChimeraX.
deep learning based prediction of structures and functional groups from MS/MS spectra
Visualize the inner workings of RNA bioinformatics algorithms for structure prediction, interaction prediction and sequence alignment.
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