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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 3
771-775

Survival analysis algorithm based on multi-omics data and variational sparse autoencoder

Yin Qingyana
Wu Ruipinga
Chen Wangwanga
Bian Genqingb
a. School of Science, b. School of Information & Control Engineering, Xi'an University of Architecture & Technology, Xi'an 710055, China
DOI: 10.19734/j.issn.1001-3695.2022.07.0361

Abstract

Aiming at the curse of dimensionality and overfitting issues caused by multi-omics data for survival analysis, this paper proposed a survival analysis model based on multi-omics data and sparse variational autoencoder, called VAESCox. The algorithm combined the basic structure of variational autoencoder with sparse coding and survival analysis, trained the variational autoencoder to learn low-dimensional representations in the unsupervised stage, transfered the trained weights to the survival analysis model, fine-tunes and sparse encodes the passed weights in the supervised stage. Experimental results show that VAESCox model achieved higher C-index values in the ablation and comparison experiments on 8 different cancer types datasets. Compared with other four baseline survival analysis methods, the proposed algorithm not only mitigates the overfitting issue of multi-omics data integration, but also significantly improves survival prediction performance, indicating that the integration of different omics data is beneficial for accurate prediction of prognostic survival outcome.

Foundation Support

国家自然科学基金资助项目(61872284,12001418)
陕西省自然科学基础研究计划面上项目(2022JM-026)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.07.0361
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 3
Section: Algorithm Research & Explore
Pages: 771-775
Serial Number: 1001-3695(2023)03-020-0771-05

Publish History

[2022-10-17] Accepted Paper
[2023-03-05] Printed Article

Cite This Article

殷清燕, 武锐萍, 陈旺旺, 等. 基于多组学数据和稀疏变分自编码器的生存分析算法 [J]. 计算机应用研究, 2023, 40 (3): 771-775. (Yin Qingyan, Wu Ruiping, Chen Wangwang, et al. Survival analysis algorithm based on multi-omics data and variational sparse autoencoder [J]. Application Research of Computers, 2023, 40 (3): 771-775. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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