GRAM-CNN specifications

Unique identifier:
OMICS_25425
Interface:
Command line interface
Operating system:
Unix/Linux
Computer skills:
Advanced
Requirements:
Tensorflow, genism, numpy: pip install numpy, pre-trained embedding
Software type:
Application/Script
Restrictions to use:
None
Programming languages:
Perl, Python
Stability:
Stable
Maintained:
Yes

versioning

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GRAM-CNN distribution

download

GRAM-CNN support

Maintainers

  • Xiaolin Li <>
  • Ana Conesa <>

forum

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Credits

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Publications

Institution(s)

National Science Foundation Center for Big Learning /University of Florida, FL, USA; Department of Computer & Information Science & Engineering / University of Florida, FL, USA; Department of Electrical and Computer Engineering / University of Florida, FL, USA; Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences / University of Florida, FL, USA; Genomics of Gene Expression Laboratory / Centro de Investigaciones Principe Felipe (CIPF), Valencia, Spain

Funding source(s)

Supported in whole by the National Institute of Food and Agriculture, U.S. Department of Agriculture (Award number 2015-70016-23029), National Science Foundation (grants ACI 1245880, ACI 1229576, CCF-1128805, CNS-1624782), and National Institutes of Health (R01GM110240).

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