Git Product home page Git Product logo

qbic-pred's Introduction

QBiC-Pred (Quantitative predictions of transcription factor binding changes due to sequence variants)

alt text

QBiC-Pred (http://qbic.genome.duke.edu/) is a web server that uses OLS 6-mer models trained on universal PBM data to predict TF binding changes due to sequence variants, as well as the significance of the changes (which implicitly depends on the quality of the data and models).

Directory structure

  1. generate_prediction This directory contains code to generate 12-mer table used by the website to make prediction
  2. website This directory contains all code files used by QBiC-Pred web server. The web server is written using Python Flask for the backend and bootstrap+Ajax for the frontend.

qbic-pred's People

Contributors

vincentiusmartin avatar jz132 avatar lriesebos avatar yangyxt avatar

Stargazers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.