Git Product home page Git Product logo
ChuNan Liu photo

biochunan Goto Github PK

followers: 10.0 following: 29.0 repos: 104.0 gists: 0.0

Name: ChuNan Liu

Type: User

Company: University College London

Bio: PhD student at UCL Computational Biology. Research focuses on developing deep learning tools for antibody development. Geometric Deep Learning, Protein LMs.

Twitter: LiuChunan

Location: London, UK

Hi there šŸ‘‹

My name is Chu'nan Liu (åˆ˜ę„šå—). I am a PhD student in bioinformatics at the University College London. I develop computational tools and build datasets to study antibody-antigen interactions. I am also interested in the application of deep learning in structural bioinformatics.

I am open to collaborations on structural bioinformatics, protein datasets, geometric deep learning, etc. Feel free to reach out via email, LinkedIn, or Twitter.

šŸ”­ Iā€™m currently working on



  • Nov 13-16, 2023: I present the above work at PEGS Europe 2023 in Lisbon, Portugal šŸ‡µšŸ‡¹.
    • šŸ“Š Check out the poster here





  • I host a 3D viewer for antibody-antigen interface analysis.
    • šŸ‘€ Check it out at AsEP

ChuNan Liu's Projects

3dmol.js icon 3dmol.js

WebGL accelerated JavaScript molecular graphics library

absplit icon absplit

Code to split an antibody PDB file into Fv fragments with their antigens

acaca icon acaca

Canonical assignment code from our 1996 paper [PMID: 8947577]

alphafold2 icon alphafold2

To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released

anarci icon anarci

Antibody Numbering and Antigen Receptor ClassIfication

attnpacker icon attnpacker

Code and Pre-Trained Models for "AttnPacker: An end-to-end deep learning method for protein side-chain packing"

bds-files icon bds-files

Supplementary files for my book, "Bioinformatics Data Skills"

bert icon bert

TensorFlow code and pre-trained models for BERT

binance icon binance

A full-featured .NET Binance API library.

d2l-en icon d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.

d2l-zh icon d2l-zh

怊åŠØę‰‹å­¦ę·±åŗ¦å­¦ä¹ ć€‹ļ¼šé¢å‘äø­ę–‡čÆ»č€…ć€čƒ½čæč”Œć€åÆč®Øč®ŗ怂äø­č‹±ę–‡ē‰ˆč¢«60多äøŖ国家ēš„400å¤šę‰€å¤§å­¦ē”ØäŗŽę•™å­¦ć€‚

d3 icon d3

Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

deepmind-research icon deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

Recommend Projects

  • React photo React

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

  • Vue.js photo Vue.js

    šŸ–– 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. šŸ“ŠšŸ“ˆšŸŽ‰

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 ā¤ļø Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.