Bioinformatics tools with deep learning based on GPU

Che Lun Hung, Chuan Yi Tang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Due to the rapid increase in biological data dimension and acquisition rate, the traditional analysis methods are unable to achieve acceptable accuracy. Recently, Deep learning technologies have shown outstanding results in many domains; especially in pattern recognition in the field of bioinformatics. In this paper, we provide background of what deep learning and its frameworks. In addition, we review the state-of-the-art algorithms based on GPU to presenting the usage of them to guide computational biologists to know how to leverage deep learning to improve their methods.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1906-1908
Number of pages3
ISBN (Electronic)9781509030491
DOIs
StatePublished - 15 Dec 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: 13 Nov 201716 Nov 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Conference

Conference2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/TerritoryUnited States
CityKansas City
Period13/11/1716/11/17

Keywords

  • Bioinformatics
  • Deep Learning
  • GPU
  • High Performance Computing

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