Title | Hierarchical DNN with Heterogeneous Computing Enabled High-Performance DNA Sequencing |
Author | |
Corresponding Author | Mei Yan; Hao Yu |
DOI | |
Publication Years | 2022
|
Conference Name | IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)
|
ISBN | 978-1-6654-5080-5
|
Source Title | |
Pages | 35-40
|
Conference Date | NOV 11-13, 2022
|
Conference Place | So Univ Sci & Technol,Shenzhen,PEOPLES R CHINA
|
Publication Place | 345 E 47TH ST, NEW YORK, NY 10017 USA
|
Publisher | |
Abstract | DNA sequencing is a popular tool to demystify the code of living organisms and is reforming the medical, pharmaceutical and biotech industries. The Next-Generation Sequencing (NGS) plays a vital role in high-throughput DNA sequencing with massively parallel data generation. Nevertheless, the massive amount of data imposes great challenges for data analysis. It is arduous to reach a low error rate for handling noisy and/or biased signals owing to the imperfect biochemical reactions and imaging systems. Furthermore, a homogeneous computing system lacks computing power and memory bandwidth. Therefore, in this work, a heterogeneous computing platform with a hierarchical deep neural network sequencing pipeline is proposed to improve the sequencing quality and increase processing speed. Experiments demonstrate that the proposed work reached higher effective throughput (12.18% more clusters found), lower error rate (0.0175%), higher quality score (%Q30 99.27%), and 19% faster. The reported work empowers virus detection, diseases diagnostic, and other potential biomedical applications. |
Keywords | |
SUSTech Authorship | Corresponding
|
Language | English
|
URL | [Source Record] |
Indexed By | |
WOS Research Area | Computer Science
; Engineering
|
WOS Subject | Computer Science, Hardware & Architecture
; Engineering, Electrical & Electronic
|
WOS Accession No | WOS:000987045300008
|
Data Source | Web of Science
|
PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10090281 |
Citation statistics |
Cited Times [WOS]:0
|
Document Type | Conference paper |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/519915 |
Department | SUSTech Institute of Microelectronics |
Affiliation | 1.GeneSense Technology Inc., Shanghai 201210 2.School of Microelectronics, Southern University of Science and Technology 3.Ministry of Education Key Laboratory of RF Circuits and Systems, Hangzhou Dianzi University |
Corresponding Author Affilication | SUSTech Institute of Microelectronics |
Recommended Citation GB/T 7714 |
Shaobo Luo,,Zhiyuan Xie,Gengxin Chen,et al. Hierarchical DNN with Heterogeneous Computing Enabled High-Performance DNA Sequencing[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:35-40.
|
Files in This Item: | ||||||
File Name/Size | DocType | Version | Access | License | ||
Hierarchical DNN wit(1754KB) | Restricted Access | -- |
|
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment