基本信息
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Bio
Research interests: Deep Learning, Computer Vision, Bioinformatics
During my PhD I proposed simplified solutions for a few important scientific problems. These include:
How to train artificial neural networks better?
Network Deconvolution
Innovated redundancy reduction in feature pixels and channels to improve the convergence of training deep neural networks.
Show a possible relation with Hubel and Wiesel's center-surround structures and sparse representations.
How to assemble genomes more efficiently?
From Long Erroneous Sequencing Data
Reduce the redundancy in the third generation sequencing data (project name: DBG2OLC). The work reduced the human genome assembly time from 405,000 CPU hours to <2000 CPU hours (or ~ 200X speedup)
The approach has been used to assemble hundreds of genomes, including apple, lamprey, fruit fly, bat.
From Short Sequencing Data
Reduce the redundancy in the de Bruijn graph representation to achieve memory-efficient genome assembly algorithm for the second-generation sequencing.
The work (project name: SparseAssembler) has reduced the computational memory requirement of this fundamental task by 90%.
This work has been adopted by BGI-Shenzhen to assemble thousands of genomes.
Research Interests
Papers共 35 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
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Danfeng Qin,Chas Leichner, Manolis Delakis,Marco Fornoni, Shixin Luo, Fan Yang,Weijun Wang,Colby Banbury,Chengxi Ye,Berkin Akin,Vaibhav Aggarwal,Tenghui Zhu,
CoRR (2024)
Cited0Views0EIBibtex
0
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Proceedings of the AAAI Conference on Artificial Intelligenceno. 8 (2021): 8849-8856
Jing Luo,Jing Chai,Yanling Wen,Min Tao,Guoliang Lin,Xiaochuan Liu,Li Ren, Zeyu Chen,Shigang Wu,Shengnan Li,Yude Wang,Qinbo Qin,
Science advancesno. 22 (2020): eaaz7677-eaaz7677
CoRR (2019)
Cited18Views0EIBibtex
18
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Nature geneticsno. 2 (2018): 270-277
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Author Statistics
#Papers: 35
#Citation: 2196
H-Index: 23
G-Index: 35
Sociability: 5
Diversity: 0
Activity: 0
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- 合作者
- 学生
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