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# OmiVAE | ||
### Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification | ||
#### Xiaoyu Zhang, Jingqing Zhang, Kai Sun, Xian Yang, Chengliang Dai, Yike Guo | ||
Accepted by 2019 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019) | ||
***Please check the updated version of OmiVAE:*** | ||
[OmiEmbed](https://github.com/zhangxiaoyu11/OmiEmbed) | ||
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[![GitHub license](https://img.shields.io/github/license/Naereen/StrapDown.js.svg)](https://github.com/zhangxiaoyu11/OmiVAE/blob/master/LICENSE) | ||
![Safe](https://img.shields.io/badge/Stay-Safe-red?logo=data:image/svg%2bxml;base64,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) | ||
[![GitHub stars](https://img.shields.io/github/stars/zhangxiaoyu11/OmiVAE.svg?style=social&label=Star&maxAge=2592000)](https://github.com/zhangxiaoyu11/OmiVAE/stargazers) | ||
[![GitHub forks](https://img.shields.io/github/forks/zhangxiaoyu11/OmiVAE.svg?style=social&label=Fork&maxAge=2592000)](https://github.com/zhangxiaoyu11/OmiVAE/network/members) | ||
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**OmiVAE: Integrated Multi-omics Analysis Using Variational Autoencoders** | ||
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**Xiaoyu Zhang** (x.zhang18@imperial.ac.uk) | ||
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Data Science Institute, Imperial College London | ||
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## Introduction | ||
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OmiVAE is an end-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets. | ||
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Accepted by 2019 IEEE International Conference on Bioinformatics and Biomedicine (**IEEE BIBM 2019**) | ||
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Paper Link: [arXiv](https://arxiv.org/abs/1908.06278) | ||
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End-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets. | ||
## Citation | ||
If you use this code for your research, please cite our paper. | ||
``` | ||
@inproceedings{OmiVAE2019, | ||
title={Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification}, | ||
author={Zhang, Xiaoyu and Zhang, Jingqing and Sun, Kai and Yang, Xian and Dai, Chengliang and Guo, Yike}, | ||
booktitle={Bioinformatics and Biomedicine (BIBM), 2019 IEEE International Conference on}, | ||
year={2019} | ||
} | ||
``` | ||
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## OmiEmbed | ||
***Please check the updated version of OmiVAE:*** | ||
[OmiEmbed](https://github.com/zhangxiaoyu11/OmiEmbed) | ||
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## License | ||
This source code is licensed under the [MIT](https://github.com/zhangxiaoyu11/OmiVAE/blob/master/LICENSE) license. | ||
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