Skip navigation
DSpace logo
  • Home
  • Browse
    • SMD
      & Institutes
    • Browse Items by:
    • Published/ Complete Date
    • Author/ PI/CoPI
    • Title
    • Keyword (Publication)
  • Sign on to:
    • My KRISHI
    • Receive email
      updates
    • Edit Profile
ICAR logo

KRISHI

ICAR RESEARCH DATA REPOSITORY FOR KNOWLEDGE MANAGEMENT
(An Institutional Publication and Data Inventory Repository)


  1. KRISHI Publication and Data Inventory Repository
  2. Horticultural Science A7
  3. ICAR-Central Plantation Crops Research Institute J6
  4. HS-CPCRI-Publication
"Not Available": Please do not remove the default option "Not Available" for the fields where metadata information is not available
"1001-01-01": Date not available or not applicable for filling metadata infromation
Please use this identifier to cite or link to this item: http://krishi.icar.gov.in/jspui/handle/123456789/13441
Title: Computational prediction and characterization of miRNA from coconut leaf transcriptome
Other Titles: Not Available
Authors: Naganeeswaran, S.
Fayas, T.P.
Rachana, K.E.
Rajesh, M.K.
ICAR Data Use Licennce: http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf
Author's Affiliated institute: ICAR::Central Plantation Crops Research Institute
Published/ Complete Date: 2015-01-01
Project Code: Not Available
Keywords: miRNAs
RNA
gene expression
in silico
miRBase
coconut
leaf transcriptome
Publisher: Not Available
Citation: Journal of Applied Horticulture, 17(1): 12-17, 2015
Series/Report no.: Not Available;
Abstract/Description: Micro RNAs (miRNAs) are single stranded, small and non-coding endogenous RNA molecules, which control the gene expression at the post-transcriptional level either by suppression or degradation. Because of its highly conserved nature, in silico methods can be employed to predict novel miRNAs in plant species. By using previously known plant miRNAs available at miRBase, we predicted 16 miRNAs, which belongs to 11 miRNA families, and also targets for seven potential miRNAs in coconut leaf transcriptome. A majority of these seem to encode transcription factors. To the best of our knowledge, this is the first report of in silico prediction and characterization of miRNA from coconut. These findings form an useful resource for future research into miRNA prediction and function prediction in coconut and for studies on their experimental validation and functional analyses.
Description: Not Available
ISSN: Not Available
Type(s) of content: Article
Sponsors: Not Available
Language: English
Name of Journal: Journal of Applied Horticulture
NAAS Rating: 5.13
Volume No.: 17(1)
Page Number: 12-17
Name of the Division/Regional Station: Not Available
Source, DOI or any other URL: Not Available
URI: http://krishi.icar.gov.in/jspui/handle/123456789/13441
Appears in Collections:HS-CPCRI-Publication

Files in This Item:
There are no files associated with this item.
Show full item record


Items in KRISHI are protected by copyright, with all rights reserved, unless otherwise indicated.

  File Downloads  

May 2022: 57561 Apr 2022: 94186 Mar 2022: 96096 Feb 2022: 93736 Jan 2022: 86503 Dec 2021: 98347

Total Download
2669542

(Also includes document to fetched through computer programme by other sites)
( From May 2017 )

ICAR Data Use Licence
Disclaimer
©  2016 All Rights Reserved  • 
Indian Council of Agricultural Research
Krishi Bhavan, Dr. Rajendra Prasad Road, New Delhi-110 001. INDIA

INDEXED BY

KRISHI: Inter Portal Harvester

DOAR
Theme by Logo CINECA Reports

DSpace Software Copyright © 2002-2013  Duraspace - Feedback