Graph-based community clustering approach to extract protein domains from a predicted aligned error matrix

Overview

pae_to_domains

Graph-based community clustering approach to extract protein domains from a predicted aligned error matrix

Overview

Using a predicted aligned error matrix corresponding to an AlphaFold2 model (e.g. as downloaded from https://alphafold.ebi.ac.uk/), returns a series of lists of residue indices, where each list corresponds to a set of residues clustering together into a pseudo-rigid domain.

Requirements

  • Python >=3.7
  • NetworkX >= 2.6.2

Known Issues

Due to an internal implementation issue in NetworkX (Issue #4992) some combinations of PAE matrix and resolution can lead to a KeyError. Solutions to this are being explored, and it will hopefully be fixed in the next NetworkX release.

Usage

While primarily intended as a code snippet to be incorporated into larger projects, this can also be called from the command line. At its simplest:

python pae_to_domains.py pae_file.json

... will yield a .csv file with each line providing the indices for one residue cluster. Full help for the command-line version:

positional arguments:
  pae_file              Name of the PAE JSON file.

optional arguments:
  -h, --help            show this help message and exit
  --output_file OUTPUT_FILE
                        Name of output file (comma-delimited text format.
                        Default: clusters.csv
  --pae_power PAE_POWER
                        Graph edges will be weighted as 1/pae**pae_power.
                        Default: 1.0
  --pae_cutoff PAE_CUTOFF
                        Graph edges will only be created for residue pairs
                        with pae

Example

Using https://alphafold.ebi.ac.uk/entry/Q9HBA0 as an example case...

resolution=0.5: Resolution 0.5, cartoon coloured by domain assignment

resolution=1.0: Resolution 1.0, cartoon coloured by domain assignment

resolution=2.0: Resolution 2.0, cartoon coloured by domain assignment

Owner
Tristan Croll
One-time chemical engineer, now full-time structural biology methods developer.
Tristan Croll
BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal Transfer

BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal Transfer Project Page | Paper | Video State-of-the-art image-to-image translatio

47 Dec 06, 2022
Self-supervised spatio-spectro-temporal represenation learning for EEG analysis

EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation This repository provides a tensorflow implementation of a submitted paper: EEG-Orie

Wonjun Ko 4 Jun 09, 2022
根据midi文件演奏“风物之诗琴”的脚本 "Windsong Lyre" auto play

Genshin-lyre-auto-play 简体中文 | English 简介 根据midi文件演奏“风物之诗琴”的脚本。由Python驱动,在此承诺, ⚠️ 项目内绝不含任何能够引起安全问题的代码。 前排提示:所有键盘在动但是原神没反应的都是因为没有管理员权限,双击run.bat或者以管理员模式

御坂17032号 386 Jan 01, 2023
BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation

BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation Installing The Dependencies $ conda create --name beametrics python

7 Jul 04, 2022
Self-Adaptable Point Processes with Nonparametric Time Decays

NPPDecay This is our implementation for the paper Self-Adaptable Point Processes with Nonparametric Time Decays, by Zhimeng Pan, Zheng Wang, Jeff M. P

zpan 2 Sep 24, 2022
A pytorch implementation of faster RCNN detection framework (Use detectron2, it's a masterpiece)

Notice(2019.11.2) This repo was built back two years ago when there were no pytorch detection implementation that can achieve reasonable performance.

Ruotian(RT) Luo 1.8k Jan 01, 2023
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective

Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective Zhengzhuo Xu, Zenghao Chai, Chun Yuan This is the PyTorch implement

Sincere 16 Dec 15, 2022
StyleGAN - Official TensorFlow Implementation

StyleGAN — Official TensorFlow Implementation Picture: These people are not real – they were produced by our generator that allows control over differ

NVIDIA Research Projects 13.1k Jan 09, 2023
PyTorch implementation of "A Two-Stage End-to-End System for Speech-in-Noise Hearing Aid Processing"

Implementation of the Sheffield entry for the first Clarity enhancement challenge (CEC1) This repository contains the PyTorch implementation of "A Two

10 Aug 19, 2022
Explanatory Learning: Beyond Empiricism in Neural Networks

Explanatory Learning This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks". Datasets Download the datasets

GLADIA Research Group 10 Dec 06, 2022
Algorithm to texture 3D reconstructions from multi-view stereo images

MVS-Texturing Welcome to our project that textures 3D reconstructions from images. This project focuses on 3D reconstructions generated using structur

Nils Moehrle 766 Jan 04, 2023
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction

FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel ga

Tarun K 280 Dec 23, 2022
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Segmentation Transformer Implementation of Segmentation Transformer in PyTorch, a new model to achieve SOTA in semantic segmentation while using trans

Abhay Gupta 161 Dec 08, 2022
Code release for BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images

BlockGAN Code release for BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images BlockGAN: Learning 3D Object-aware Scene Rep

41 May 18, 2022
Software for Multimodalty 2D+3D Facial Expression Recognition (FER) UI

EmotionUI Software for Multimodalty 2D+3D Facial Expression Recognition (FER) UI. demo screenshot (with RealSense) required packages Python = 3.6 num

Yang Jiao 2 Dec 23, 2021
Mesh TensorFlow: Model Parallelism Made Easier

Mesh TensorFlow - Model Parallelism Made Easier Introduction Mesh TensorFlow (mtf) is a language for distributed deep learning, capable of specifying

1.3k Dec 26, 2022
Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation.

Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,

29 Aug 23, 2022
Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch]

Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch] Abstract Snapshot compressive imaging (SCI) can rec

integirty 6 Nov 01, 2022
Framework web SnakeServer.

SnakeServer - Framework Web 🐍 Documentação oficial do framework SnakeServer. Conteúdo Sobre Como contribuir Enviar relatórios de segurança Pull reque

Jaedson Silva 0 Jul 21, 2022
Pytorch reimplementation of the Mixer (MLP-Mixer: An all-MLP Architecture for Vision)

MLP-Mixer Pytorch reimplementation of Google's repository for the MLP-Mixer (Not yet updated on the master branch) that was released with the paper ML

Eunkwang Jeon 18 Dec 08, 2022