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

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.
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

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

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

Deep Learning with PyTorch made easy ๐Ÿš€ !

Deep Learning with PyTorch made easy ๐Ÿš€ ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c

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.
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

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.

PyTorch package for the discrete VAE used for DALLยทE.

Overview [Blog] [Paper] [Model Card] [Usage] This is the official PyTorch package for the discrete VAE used for DALLยทE. Installation Before running th

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

PyVarInf PyVarInf provides facilities to easily train your PyTorch neural network models using variational inference. Bayesian Deep Learning with Vari

quantize aware training package for NCNN on pytorch

ncnnqat ncnnqat is a quantize aware training package for NCNN on pytorch. Table of Contents ncnnqat Table of Contents Installation Usage Code Examples

Comments
  • Fixing a bug in sequence preprocessing

    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?

    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
Releases(0.0.3)
Owner
Phil Wang
Working with Attention. It's all we need.
Phil Wang
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

Simon Blanke 422 Jan 4, 2023
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

This project is now archived. It's been fun working on it, but it's time for me to move on. Thank you for all the support and feedback over the last c

Max Pumperla 2.1k Jan 3, 2023
Convenient tool for speeding up the intern/officer review process.

icpc-app-screen Convenient tool for speeding up the intern/officer applicant review process. Eliminates the pain from reading application responses of

null 1 Oct 30, 2021
Bib-parser - Convenient script to parse .bib files with the ACM Digital Library like metadata

Bib Parser Convenient script to parse .bib files with the ACM Digital Library li

Mehtab Iqbal (Shahan) 1 Jan 26, 2022
Official Pytorch implementation of 'GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network' (NeurIPS 2020)

Official implementation of GOCor This is the official implementation of our paper : GOCor: Bringing Globally Optimized Correspondence Volumes into You

Prune Truong 71 Nov 18, 2022
MADE (Masked Autoencoder Density Estimation) implementation in PyTorch

pytorch-made This code is an implementation of "Masked AutoEncoder for Density Estimation" by Germain et al., 2015. The core idea is that you can turn

Andrej 498 Dec 30, 2022
Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch

Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c

Phil Wang 22 Oct 28, 2022
ALBERT-pytorch-implementation - ALBERT pytorch implementation

ALBERT-pytorch-implementation developing... ๋ชจ๋ธ์˜ ๊ฐœ๋…์ดํ•ด๋ฅผ ๋•๊ธฐ ์œ„ํ•œ ๊ตฌํ˜„๋ฌผ๋กœ ํ˜„์žฌ ๋ณ€์ˆ˜๋ช…์„ ์ƒ์„ธํžˆ ์ ์—ˆ๊ณ 

BG Kim 3 Oct 6, 2022
An AutoML Library made with Optuna and PyTorch Lightning

An AutoML Library made with Optuna and PyTorch Lightning Installation Recommended pip install -U gradsflow From source pip install git+https://github.

GradsFlow 294 Dec 17, 2022
Turning SymPy expressions into PyTorch modules.

sympytorch A micro-library as a convenience for turning SymPy expressions into PyTorch Modules. All SymPy floats become trainable parameters. All SymP

Patrick Kidger 89 Dec 13, 2022