GRAM-CNN specifications


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




No version available


  • person_outline Xiaolin Li <>
  • person_outline Ana Conesa <>

Publication for GRAM-CNN

GRAM-CNN 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
GRAM-CNN 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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