DUDE-Seq specifications

Unique identifier:
OMICS_19919
Interface:
Web user interface
Input format:
FASTA, FASTQ
Computer skills:
Basic
Maintained:
Yes
Name:
Discrete Universal Denoiser-Sequence
Restrictions to use:
None
Programming languages:
C, C++, Python
Stability:
Stable

DUDE-Seq specifications

Unique identifier:
OMICS_19919
Software type:
Pipeline/Workflow
Restrictions to use:
None
Programming languages:
C, C++, Python
Stability:
Stable
Name:
Discrete Universal Denoiser-Sequence
Interface:
Command line interface
Operating system:
Windows
Computer skills:
Basic
Maintained:
Yes

versioning

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DUDE-Seq distribution

download

DUDE-Seq support

Maintainers

  • Sungroh Yoon <>
  • Taesup Moon <>
  • Sungroh Yoon <>
  • Taesup Moon <>

Additional information

The desktop version is available at: https://github.com/datasnu/dude-seq The web application is available at: http://data.snu.ac.kr/pub/dude-seq/#

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Credits

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Publications

Institution(s)

Electrical and Computer Engineering, Seoul National University, Seoul, Korea; College of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea; Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA; Electrical Engineering, Stanford University, Stanford, CA, USA

Funding source(s)

Supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science, ICT and Future Planning) [2014M3A9E2064434 and 2016M3A7B4911115], in part by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare [HI14C3405030014], in part by the Basic Science Research Program through the National Research Foundation of Korea [NRF-2016R1C1B2012170], in part by the ICT R&D program of MSIP/IITP [2016-0-00563, Research on Adaptive Machine Learning Technology Development for Intelligent Autonomous Digital Companion], and in part by NIH Grant 5U01CA198943-03.

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