Deep clustering of scRNA-seq data

Deep-Learning framework for multi-omic and survival data integration

Deep Batch Integration and Denoise of Single-Cell RNA-seq Data

DEGAS is an R package that can be used to prioritize cells in relation to disease.

可能是最好的PySide6中文教程！用代码实例讲解PySide6，附优质Demos、图标库、QSS皮肤、相关文章等分享！

Accurate ADMET Prediction with XGBoost

🔥 🌟⭐⭐⭐ ⭐ 史上最全的BAT大厂Android面试题汇集，以及常用的Android开发的一些技能点，冷门知识点汇总，开发中遇到的坑汇总等干货。

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

PyTorch tutorials, examples and some books I found 【不定期更新】整理的PyTorch 最新版教程、例子和书籍

Multiscale embedded gene co-expression network analysis

MOCO-GCN consists of two main components: a Two-view Co-training Graph Convolutional Networks (GCNs) module that learns different omics data features by distilling knowledge from each other and a V…

MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations

MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.

making the code compatible with tensorflow 2

scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics

A universal framework for single-cell multi-omics data integration with graph convolutional networks

Multi-Dimensional Constrained Joint Non-Negative Matrix Factorization

R toolkit for single cell genomics

Single-nuclei RNA-seq and ATAC-seq in Alzheimer's disease

上海海事大学 LaTeX 学位论文模板

Graph-linked unified embedding for single-cell multi-omics data integration

R toolkit for the analysis of single-cell chromatin data