The Advances and Challenges of Deep Learning Application in Biological Big Data Processing

Title:The Advances and Challenges of Deep Learning Application in Biological Big Data Processing

Volume: 13 Issue: 4

Author(s): Li Peng, Manman Peng*, Bo Liao, Guohua Huang*, Weibiao Li and Dingfeng Xie

Affiliation:

• College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082,China

• College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082,China

Keywords: Deep learning, machine learning, big data, bioinformatics, biological image.

Abstract: Background: Bioinformatics research comes into an era of big data. Mining potential value in biological big data for scientific research and health care field has the vital significance. Deep learning as new machine learning algorithms, on the basis of big data and high performance distributed parallel computing, show the excellent performance in biological big data processing.

Objective: Provides a valuable reference for researchers to use deep learning in their studies of processing large biological data.

Methods: This paper introduces the new model of data storage and computational facilities for big data analyzing. Then, the application of deep learning in three aspects including biological omics data processing, biological image processing and biomedical diagnosis was summarized. Aiming at the problem of large biological data processing, the accelerated methods of deep learning model have been described.

Conclusion: The paper summarized the new storage mode, the existing methods and platforms for biological big data processing, and the progress and challenge of deep learning applies in biological big data processing.

Cite this article as:

Peng Li , Peng Manman *, Liao Bo , Huang Guohua *, Li Weibiao and Xie Dingfeng , The Advances and Challenges of Deep Learning Application in Biological Big Data Processing, Current Bioinformatics 2018; 13 (4) . https://dx.doi.org/10.2174/1574893612666170707095707