PLncPRO specifications


Unique identifier OMICS_22060
Name PLncPRO
Alternative name Plant Long Non-Coding RNA Prediction by Random fOrest
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input data A set of training transcript sequences.
Output data The random forest model.
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Version 1.1
Stability Stable
Requirements NCBI BLAST, framefinder, GNU C Library, NumPy, SciPy, Biopython, Scikit-learn
Maintained Yes



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  • person_outline Mukesh Jain <>
  • person_outline Urminder Singh <>

Publication for Plant Long Non-Coding RNA Prediction by Random fOrest

PLncPRO institution(s)
School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India; Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Gautam Buddha Nagar, India
PLncPRO funding source(s)
Supported by Department of Science & Technology, Government of India, under the Promotion of University Research and Scientific Excellence (PURSE) grant (Phase II) scheme to the Jawaharlal Nehru University, New Delhi and Department of Biotechnology, Government of India under Centre of Excellence in Bioinformatics to the School of Computational & Integrative Sciences.

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