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liuz-bio's Projects

ckg icon ckg

Clinical Knowledge Graph (CKG) is a platform with twofold objective: 1) build a graph database with experimental data and data imported from diverse biomedical databases 2) automate knowledge discovery making use of all the information contained in the graph

drkg icon drkg

A knowledge graph and a set of tools for drug repurposing

fitlog icon fitlog

fitlog是一款在深度学习训练中用于辅助用户记录日志和管理代码的工具

hello-algo icon hello-algo

《Hello 算法》:动画图解、一键运行的数据结构与算法教程,支持 Java, C++, Python, Go, JS, TS, C#, Swift, Rust, Dart, Zig 等语言。

hrgat icon hrgat

The code for hyper-node relational graph attention network

mkdocs icon mkdocs

Project documentation with Markdown.

modbamtools icon modbamtools

Set of tools to manipulate and visualize modified base bam files

multi-view-image-classification icon multi-view-image-classification

This repository presents a couple of approaches to the problem of multi-view image classification. I faced this challenge during a hackathon in which I participated, and decided to share my code here. I've also written a Medium article to provide further details and explanations. Feel free to check it out !

ngmlr icon ngmlr

NGMLR is a long-read mapper designed to align PacBio or Oxford Nanopore (standard and ultra-long) to a reference genome with a focus on reads that span structural variations

nlp-tutorial icon nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

openke icon openke

An Open-Source Package for Knowledge Embedding (KE)

pggb icon pggb

the pangenome graph builder

pong icon pong

Fast analysis and visualization of latent clusters in population genetic data

pophelper icon pophelper

An R package to analyse and visualise admixture proportions from STRUCTURE, fastSTRUCTURE, TESS, ADMIXTURE etc.

proephoreseqdata icon proephoreseqdata

In this paper, the physiological and proteomic responses in leaves of A. mira were investigated during the period of drought and recovery.

pytorch-handbook icon pytorch-handbook

pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行

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