trRosetta | predict protein inter-residue geometries | Genomics library

by gjoni Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | trRosetta Summary

trRosetta is a Python library typically used in Artificial Intelligence, Genomics, Deep Learning applications. trRosetta has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However trRosetta build file is not available. You can download it from GitHub.

This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicted inter-residue orientations. It includes tools to predict protein inter-residue geometries from a multiple sequence alignment or a single sequence. Contact: Ivan Anishchenko, aivan@uw.edu.

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Support

trRosetta has a low active ecosystem.

It has 135 star(s) with 34 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 10 have been closed. On average issues are closed in 49 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of trRosetta is current.

Quality

trRosetta has no bugs reported.

Security

trRosetta has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

trRosetta is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

trRosetta releases are not available. You will need to build from source code and install.

trRosetta has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed trRosetta and discovered the below as its top functions. This is intended to give you an instant insight into trRosetta implemented functionality, and help decide if they suit your requirements.

Load weights from RAM .
Compute the covariance matrix .
Parse A3M file .
Get arguments .
get command line arguments
Compute reweighted weight .
Compute pssm .
Instance Normalization .
2d convolution layer .

Get all kandi verified functions for this library.

trRosetta Key Features

No Key Features are available at this moment for trRosetta.

trRosetta Examples and Code Snippets

No Code Snippets are available at this moment for trRosetta.

Community Discussions

Trending Discussions on trRosetta

TensorFlow DLL load failed: The specified module could not be found

QUESTION

TensorFlow DLL load failed: The specified module could not be found

Asked 2021-Jun-07 at 13:48

Trying to run python in terminal, already done:

...

ANSWER

Answered 2021-Jun-07 at 13:48

CPU's with no AVX support are no longer supported by the default tensorflow package. But there is a workaround either you have to compile from source or use google colaboratory to work. For more information you can refer here.

Source https://stackoverflow.com/questions/67730159

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install trRosetta

You can download it from GitHub.
You can use trRosetta like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.