Implementation of trRosetta and trDesign for Pytorch, made into a convenient package

Last update: Dec 17, 2022

Overview

trRosetta - Pytorch (wip)

Implementation of trRosetta and trDesign for Pytorch, made into a convenient package, for protein structure prediction and design. Will also contain an experimental version of trRosetta that uses attention. The concept of trDesign will also be abstracted into a wrapper in this repository, so that it can be applied to Alphafold2 once it is replicated. Please join the efforts there if you would like to see this happen!

The original repository can be found here

Install

$ pip install tr-rosetta-pytorch

Usage

As a command-line tool, to run a structure prediction

$ tr_rosetta <input-file.a3m>

Code

import torch
from tr_rosetta_pytorch import trRosettaNetwork

model = trRosettaNetwork(
    filters = 64,
    kernel = 3,
    num_layers = 61
).cuda()

x = torch.randn(1, 526, 140, 140).cuda()

theta, phi, distance, omega = model(x)

Citations

@article {Yang1496,
    author = {Yang, Jianyi and Anishchenko, Ivan and Park, Hahnbeom and Peng, Zhenling and Ovchinnikov, Sergey and Baker, David},
    title = {Improved protein structure prediction using predicted interresidue orientations},
    URL = {https://www.pnas.org/content/117/3/1496},
    eprint = {https://www.pnas.org/content/117/3/1496.full.pdf},
    journal = {Proceedings of the National Academy of Sciences}
}

@article {Anishchenko2020.07.22.211482,
    author = {Anishchenko, Ivan and Chidyausiku, Tamuka M. and Ovchinnikov, Sergey and Pellock, Samuel J. and Baker, David},
    title = {De novo protein design by deep network hallucination},
    URL = {https://www.biorxiv.org/content/early/2020/07/23/2020.07.22.211482},
    eprint = {https://www.biorxiv.org/content/early/2020/07/23/2020.07.22.211482.full.pdf},
    journal = {bioRxiv}
}

You might also like...

PyTorch evaluation code for Delving Deep into the Generalization of Vision Transformers under Distribution Shifts.

Out-of-distribution Generalization Investigation on Vision Transformers This repository contains PyTorch evaluation code for Delving Deep into the Gen

72 Dec 13, 2022

This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer

11 Mar 20, 2022

PyTorch deep learning projects made easy.

PyTorch Template Project PyTorch deep learning project made easy. PyTorch Template Project Requirements Features Folder Structure Usage Config file fo

3.8k Jan 1, 2023

Deep Learning with PyTorch made easy 🚀 !

Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c

381 Dec 22, 2022

tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

2.8k Jan 8, 2023

Kindle is an easy model build package for PyTorch.

Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? when we can simply build a model with yaml markup file. Kindle builds a model with no code but yaml file which its method is inspired from YOLOv5.

77 Nov 11, 2022

Comments

Fixing a bug in sequence preprocessing

When cuda is available, and a sequence of length = 1 is loaded, it is left on the cpu and not copied to the gpu. That creates an error: RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking arugment for argument tensors in method wrapper__cat)

opened by LiorZ 0
How to get a PDB file via a FASTA file?

Hello, I have recently needed to make structural predictions on many small proteins, I only have their sequence, I hope to get .PDB file, can this software implement? I tried it, it seems that I can only get the .npz file. If you can, please tell me , thank you !

opened by mooerccx 0

Implementation of trRosetta and trDesign for Pytorch, made into a convenient package

Related tags

Overview

trRosetta - Pytorch (wip)

Install

Usage

Code

Citations

You might also like...

PyTorch evaluation code for Delving Deep into the Generalization of Vision Transformers under Distribution Shifts.

This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch deep learning projects made easy.

Deep Learning with PyTorch made easy 🚀 !

tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.

Kindle is an easy model build package for PyTorch.

PyTorch package for the discrete VAE used for DALL·E.

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

quantize aware training package for NCNN on pytorch

Comments

Fixing a bug in sequence preprocessing

How to get a PDB file via a FASTA file?

Releases(0.0.3)

0.0.3(Aug 27, 2021)

0.0.2(Feb 20, 2021)

0.0.1(Feb 5, 2021)

Owner

Phil Wang

FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection

Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis

Pytorch implementation for RelTransformer

网络协议2天集训

Data stream analytics: Implement online learning methods to address concept drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" accepted in IEEE GlobeCom 2021.

Official Repo for ICCV2021 Paper: Learning to Regress Bodies from Images using Differentiable Semantic Rendering

🥇 LG-AI-Challenge 2022 1위 솔루션 입니다.

Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".

CNN designed for pansharpening

Unofficial TensorFlow implementation of the Keyword Spotting Transformer model

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.

All the code and files related to the MI-Lab of UE19CS305 course in sem 5

[SIGGRAPH'22] StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets

Projects of Andfun Yangon

Price-Prediction-For-a-Dream-Home - A machine learning based linear regression trained model for house price prediction.

Code for the paper titled "Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks" (NeurIPS 2021 Spotlight).

Dogs classification with Deep Metric Learning using some popular losses

Experiments with Fourier layers on simulation data.

Optimizing Deeper Transformers on Small Datasets