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

CVPR 2020 oral paper: Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax.

Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax ⚠️ Latest: Current repo is a complete version. But we delet

FishYuLi 341 Dec 23, 2022
In this tutorial, you will perform inference across 10 well-known pre-trained object detectors and fine-tune on a custom dataset. Design and train your own object detector.

Object Detection Object detection is a computer vision task for locating instances of predefined objects in images or videos. In this tutorial, you wi

Ibrahim Sobh 62 Dec 25, 2022
D2Go is a toolkit for efficient deep learning

D2Go D2Go is a production ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms. W

Facebook Research 744 Jan 04, 2023
Official Implementation for Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation We present a generic image-to-image translation framework, pixel2style2pixel (pSp

2.8k Dec 30, 2022
Collective Multi-type Entity Alignment Between Knowledge Graphs (WWW'20)

CG-MuAlign A reference implementation for "Collective Multi-type Entity Alignment Between Knowledge Graphs", published in WWW 2020. If you find our pa

Bran Zhu 28 Dec 11, 2022
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations

Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations This repo contains official code for the NeurIPS 2021 paper Imi

Jiayao Zhang 2 Oct 18, 2021
NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch

NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch, train it, collect statistics, and share it among the members of the community. It is not just a visual

HTM Community 93 Sep 30, 2022
Part-Aware Data Augmentation for 3D Object Detection in Point Cloud

Part-Aware Data Augmentation for 3D Object Detection in Point Cloud This repository contains a reference implementation of our Part-Aware Data Augment

Jaeseok Choi 62 Jan 03, 2023
Approaches to modeling terrain and maps in python

topography 🌎 Contains different approaches to modeling terrain and topographic-style maps in python Features Inverse Distance Weighting (IDW) A given

John Gutierrez 1 Aug 10, 2022
TensorFlow (Python API) implementation of Neural Style

neural-style-tf This is a TensorFlow implementation of several techniques described in the papers: Image Style Transfer Using Convolutional Neural Net

Cameron 3.1k Jan 02, 2023
Official repository for "Orthogonal Projection Loss" (ICCV'21)

Orthogonal Projection Loss (ICCV'21) Kanchana Ranasinghe, Muzammal Naseer, Munawar Hayat, Salman Khan, & Fahad Shahbaz Khan Paper Link | Project Page

Kanchana Ranasinghe 83 Dec 26, 2022
[ICLR'19] Trellis Networks for Sequence Modeling

TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico

CMU Locus Lab 460 Oct 13, 2022
Official repo for QHack—the quantum machine learning hackathon

Note: This repository has been frozen while we consider the submissions for the QHack Open Hackathon. We hope you enjoyed the event! Welcome to QHack,

Xanadu 118 Jan 05, 2023
A collection of educational notebooks on multi-view geometry and computer vision.

Multiview notebooks This is a collection of educational notebooks on multi-view geometry and computer vision. Subjects covered in these notebooks incl

Max 65 Dec 09, 2022
Distance correlation and related E-statistics in Python

dcor dcor: distance correlation and related E-statistics in Python. E-statistics are functions of distances between statistical observations in metric

Carlos Ramos Carreño 108 Dec 27, 2022
This repository contains code from the paper "TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network"

TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network This repository contains code from the paper "TTS-GAN: A Transformer-based Tim

Intelligent Multimodal Computing and Sensing Laboratory (IMICS Lab) - Texas State University 108 Dec 29, 2022
Training PSPNet in Tensorflow. Reproduce the performance from the paper.

Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support

Li Xuhong 126 Jul 13, 2022
A baseline code for VSPW

A baseline code for VSPW Preparation Download VSPW dataset The VSPW dataset with extracted frames and masks is available here.

28 Aug 22, 2022
[ICCV2021] Official Pytorch implementation for SDGZSL (Semantics Disentangling for Generalized Zero-Shot Learning)

Semantics Disentangling for Generalized Zero-shot Learning This is the official implementation for paper Zhi Chen, Yadan Luo, Ruihong Qiu, Zi Huang, J

25 Dec 06, 2022
Autonomous Movement from Simultaneous Localization and Mapping

Autonomous Movement from Simultaneous Localization and Mapping About us Built by a group of Clarkson University students with the help from Professor

14 Nov 07, 2022