NNR conformation conditional and global probabilities estimation and analysis in peptides or proteins fragments

Overview

NNR and global probabilities estimation and analysis in peptides or protein fragments

This module calculates global and NNR conformation dependent probabilites in each peptide residue.

First, workflow.sh bash script creates a workspace where results folder and dihedral angles .dat file are generated.

After that, Python module obtains bidimensional arrays and probabilities about conformation population and structure combinations in global and NNR Conformation conditional methods.

Specifically, global_arrays.py and conditional_arrays.py generate the 2d arrays where dihedral angles value in each point is contained. Later, this arrays are used to calculate alpha, ppII, beta and remaining probabilities. In the first place, combinations probabilities are obtained by global_probabilities.py, directe_conditional_probabilities.py, inverse_conditional_probabilities.py. The programm it is called comparition.py joins this probabilities in a single file. On the other hand, population.py calculates global and conditional probabilites for each residue. This scripts create a csv file for each residue.

Finally, R Markdown file (data_representation.Rmd) contains code chunks to represent graphically combination probabilites, population data and Ramachandran plots. In particular, this scripts export each graphic in a png file.

In this case, the data used for the example output files was from penta-alanine simulation.

Ramachandran plot

Conformation populations

Combination probabilities

Rasterize with the least efforts for researchers.

utils3d Rasterize and do image-based 3D transforms with the least efforts for researchers. Based on numpy and OpenGL. It could be helpful when you wan

Ruicheng Wang 8 Dec 15, 2022
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020

Phillip Lippe 1.1k Jan 07, 2023
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"

Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http

chenm 253 Dec 08, 2022
ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection

ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection This repository contains implementation of the

Visual Understanding Lab @ Samsung AI Center Moscow 190 Dec 30, 2022
Python implementation of "Elliptic Fourier Features of a Closed Contour"

PyEFD An Python/NumPy implementation of a method for approximating a contour with a Fourier series, as described in [1]. Installation pip install pyef

Henrik Blidh 71 Dec 09, 2022
An Unpaired Sketch-to-Photo Translation Model

Unpaired-Sketch-to-Photo-Translation We have released our code at https://github.com/rt219/Unsupervised-Sketch-to-Photo-Synthesis This project is the

38 Oct 28, 2022
RL algorithm PPO and IRL algorithm AIRL written with Tensorflow.

RL algorithm PPO and IRL algorithm AIRL written with Tensorflow. They have a parallel sampling feature in order to increase computation speed (especially in high-performance computing (HPC)).

Fangjian Li 3 Dec 28, 2021
Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data based on Pytorch Framework

VFedPCA+VFedAKPCA This is the official source code for the Paper: Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-

John 9 Sep 18, 2022
Infrastructure as Code (IaC) for a self-hosted version of Gnosis Safe on AWS

Welcome to Yearn Gnosis Safe! Setting up your local environment Infrastructure Deploying Gnosis Safe Prerequisites 1. Create infrastructure for secret

Numan 16 Jul 18, 2022
Location-Sensitive Visual Recognition with Cross-IOU Loss

The trained models are temporarily unavailable, but you can train the code using reasonable computational resource. Location-Sensitive Visual Recognit

Kaiwen Duan 146 Dec 25, 2022
Official code repository for ICCV 2021 paper: Gravity-Aware Monocular 3D Human Object Reconstruction

GraviCap Official code repository for ICCV 2021 paper: Gravity-Aware Monocular 3D Human Object Reconstruction. Gravity-Aware Monocular 3D Human-Object

Rishabh Dabral 15 Dec 09, 2022
Code and Data for NeurIPS2021 Paper "A Dataset for Answering Time-Sensitive Questions"

Time-Sensitive-QA The repo contains the dataset and code for NeurIPS2021 (dataset track) paper Time-Sensitive Question Answering dataset. The dataset

wenhu chen 35 Nov 14, 2022
This repository contains the accompanying code for Deep Virtual Markers for Articulated 3D Shapes, ICCV'21

Deep Virtual Markers This repository contains the accompanying code for Deep Virtual Markers for Articulated 3D Shapes, ICCV'21 Getting Started Get sa

KimHyomin 45 Oct 07, 2022
EM-POSE 3D Human Pose Estimation from Sparse Electromagnetic Trackers.

EM-POSE: 3D Human Pose Estimation from Sparse Electromagnetic Trackers This repository contains the code to our paper published at ICCV 2021. For ques

Facebook Research 62 Dec 14, 2022
3D position tracking for soccer players with multi-camera videos

This repo contains a full pipeline to support 3D position tracking of soccer players, with multi-view calibrated moving/fixed video sequences as inputs.

Yuchang Jiang 72 Dec 27, 2022
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels

The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels

13 Dec 22, 2022
Official implementation of "Generating 3D Molecules for Target Protein Binding"

Generating 3D Molecules for Target Protein Binding This is the official implementation of the GraphBP method proposed in the following paper. Meng Liu

DIVE Lab, Texas A&M University 74 Dec 07, 2022
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Rao Muhammad Umer 6 Nov 14, 2022
Hydra: an Extensible Fuzzing Framework for Finding Semantic Bugs in File Systems

Hydra: An Extensible Fuzzing Framework for Finding Semantic Bugs in File Systems Paper Finding Semantic Bugs in File Systems with an Extensible Fuzzin

gts3.org (<a href=[email protected])"> 129 Dec 15, 2022
Implementation of the paper All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

SemCo The official pytorch implementation of the paper All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

42 Nov 14, 2022