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

A ssl analyzer which could analyzer target domain's certificate.

ssl_analyzer A ssl analyzer which could analyzer target domain's certificate. Analyze the domain name ssl certificate information according to the inp

vincent 17 Dec 12, 2022
Applying curriculum to meta-learning for few shot classification

Curriculum Meta-Learning for Few-shot Classification We propose an adaptation of the curriculum training framework, applicable to state-of-the-art met

Stergiadis Manos 3 Oct 25, 2022
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

AstraZeneca 79 Jan 05, 2023
PyTorch implementation of Deep HDR Imaging via A Non-Local Network (TIP 2020).

NHDRRNet-PyTorch This is the PyTorch implementation of Deep HDR Imaging via A Non-Local Network (TIP 2020). 0. Differences between Original Paper and

Yutong Zhang 1 Mar 01, 2022
Imaging, analysis, and simulation software for radio interferometry

ehtim (eht-imaging) Python modules for simulating and manipulating VLBI data and producing images with regularized maximum likelihood methods. This ve

Andrew Chael 5.2k Dec 28, 2022
Geometry-Free View Synthesis: Transformers and no 3D Priors

Geometry-Free View Synthesis: Transformers and no 3D Priors Geometry-Free View Synthesis: Transformers and no 3D Priors Robin Rombach*, Patrick Esser*

CompVis Heidelberg 293 Dec 22, 2022
A collection of papers about Transformer in the field of medical image analysis.

A collection of papers about Transformer in the field of medical image analysis.

Junyu Chen 377 Jan 05, 2023
Code for "Localization with Sampling-Argmax", NeurIPS 2021

Localization with Sampling-Argmax [Paper] [arXiv] [Project Page] Localization with Sampling-Argmax Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-

JeffLi 71 Dec 17, 2022
Codes to calculate solar-sensor zenith and azimuth angles directly from hyperspectral images collected by UAV. Works only for UAVs that have high resolution GNSS/IMU unit.

UAV Solar-Sensor Angle Calculation Table of Contents About The Project Built With Getting Started Prerequisites Installation Datasets Contributing Lic

Sourav Bhadra 1 Jan 15, 2022
PyTorch Implementation of PIXOR: Real-time 3D Object Detection from Point Clouds

PIXOR: Real-time 3D Object Detection from Point Clouds This is a custom implementation of the paper from Uber ATG using PyTorch 1.0. It represents the

Philip Huang 270 Dec 14, 2022
Chinese named entity recognization with BiLSTM using Keras

Chinese named entity recognization (Bilstm with Keras) Project Structure ./ ├── README.md ├── data │   ├── README.md │   ├── data 数据集 │   │   ├─

1 Dec 17, 2021
Implementation of "Glancing Transformer for Non-Autoregressive Neural Machine Translation"

GLAT Implementation for the ACL2021 paper "Glancing Transformer for Non-Autoregressive Neural Machine Translation" Requirements Python = 3.7 Pytorch

117 Jan 09, 2023
Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions

Siren: Implicit Neural Representations with Periodic Activation Functions The unofficial Tensorflow 2 implementation of the paper Implicit Neural Repr

Seyma Yucer 2 Jun 27, 2022
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Hongje Seong 72 Dec 14, 2022
clustimage is a python package for unsupervised clustering of images.

clustimage The aim of clustimage is to detect natural groups or clusters of images. Image recognition is a computer vision task for identifying and ve

Erdogan Taskesen 52 Jan 02, 2023
PAMI stands for PAttern MIning. It constitutes several pattern mining algorithms to discover interesting patterns in transactional/temporal/spatiotemporal databases

Introduction PAMI stands for PAttern MIning. It constitutes several pattern mining algorithms to discover interesting patterns in transactional/tempor

RAGE UDAY KIRAN 43 Jan 08, 2023
Video Corpus Moment Retrieval with Contrastive Learning (SIGIR 2021)

Video Corpus Moment Retrieval with Contrastive Learning PyTorch implementation for the paper "Video Corpus Moment Retrieval with Contrastive Learning"

ZHANG HAO 42 Dec 29, 2022
"NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search".

NAS-Bench-301 This repository containts code for the paper: "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search". The

AutoML-Freiburg-Hannover 57 Nov 30, 2022
SwinTrack: A Simple and Strong Baseline for Transformer Tracking

SwinTrack This is the official repo for SwinTrack. A Simple and Strong Baseline Prerequisites Environment conda (recommended) conda create -y -n SwinT

LitingLin 196 Jan 04, 2023
Implementation of ICCV2021(Oral) paper - VMNet: Voxel-Mesh Network for Geodesic-aware 3D Semantic Segmentation

VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation Created by Zeyu HU Introduction This work is based on our paper VMNet: Voxel-Mes

HU Zeyu 82 Dec 27, 2022