FAhtisham / NP-BERT

NP-BERT is a method for identifying nucleosome positioning across 12 datasets. NP-BERT utilizes state of the art BERT models to learn features from the DNA sequences for nucleomse positioning predictions.

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NP-BERT

NP-BERT is a method for identifying nucleosome positioning across 12 datasets. NP-BERT utilizes state of the art BERT models to learn features from the DNA sequences for nucleomse positioning predictions.

Table of Contents

General Information

  • Provide general information about your project here.
  • What problem does it (intend to) solve?
  • What is the purpose of your project?
  • Why did you undertake it?

Technologies Used

  • Python 3.6
  • SLRUM if the automation of the training process is required.
  • PSI-CD-HIT (if dataset similarity check is of interest)

Features

List the ready features here:

  • Awesome feature 1
  • Awesome feature 2
  • Awesome feature 3

Screenshots

Example screenshot

Setup

What are the project requirements/dependencies? Where are they listed? A requirements.txt or a Pipfile.lock file perhaps? Where is it located?

Proceed to describe how to install / setup one's local environment / get started with the project.

Usage

How does one go about using it? Provide various use cases and code examples here.

write-your-code-here

Project Status

Project is: in progress / complete / no longer being worked on. If you are no longer working on it, provide reasons why.

Room for Improvement

Include areas you believe need improvement / could be improved. Also add TODOs for future development.

Room for improvement:

  • Improvement to be done 1
  • Improvement to be done 2

To do:

  • Feature to be added 1
  • Feature to be added 2

Acknowledgements

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  • This project was inspired by...
  • This project was based on this tutorial.
  • Many thanks to...

Contact

Created by @flynerdpl - feel free to contact me!

About

NP-BERT is a method for identifying nucleosome positioning across 12 datasets. NP-BERT utilizes state of the art BERT models to learn features from the DNA sequences for nucleomse positioning predictions.

License:GNU General Public License v3.0