KRISHI
ICAR RESEARCH DATA REPOSITORY FOR KNOWLEDGE MANAGEMENT
(An Institutional Publication and Data Inventory Repository)
"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
"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/123456789/73716| Title: | miRNALoc: predicting miRNA subcellular localizations based on principal component scores of physico-chemical properties and pseudo compositions of di-nucleotides |
| Other Titles: | Not Available |
| Authors: | Prabina Kumar Meher Subhrajit Satpathy Atmakuri Ramakrishna Rao |
| ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
| Author's Affiliated institute: | ICAR::Indian Agricultural Statistics Research Institute |
| Published/ Complete Date: | 2020-09-03 |
| Project Code: | Not Available |
| Keywords: | MicroRNAs homeostasis subcellular nucleotides |
| Publisher: | Not Available |
| Citation: | Meher, P.K., Satpathy, S. & Rao, A.R. miRNALoc: predicting miRNA subcellular localizations based on principal component scores of physico-chemical properties and pseudo compositions of di-nucleotides. Sci Rep 10, 14557 (2020). https://doi.org/10.1038/s41598-020-71381-4 |
| Series/Report no.: | Not Available; |
| Abstract/Description: | MicroRNAs (miRNAs) are one kind of non-coding RNA, play vital role in regulating several physiological and developmental processes. Subcellular localization of miRNAs and their abundance in the native cell are central for maintaining physiological homeostasis. Besides, RNA silencing activity of miRNAs is also influenced by their localization and stability. Thus, development of computational method for subcellular localization prediction of miRNAs is desired. In this work, we have proposed a computational method for predicting subcellular localizations of miRNAs based on principal component scores of thermodynamic, structural properties and pseudo compositions of di-nucleotides. Prediction accuracy was analyzed following fivefold cross validation, where ~ 63-71% of AUC-ROC and ~ 69-76% of AUC-PR were observed. While evaluated with independent test set, > 50% localizations were found to be correctly predicted. Besides, the developed computational model achieved higher accuracy than the existing methods. A user-friendly prediction server "miRNALoc" is freely accessible at https://cabgrid.res.in:8080/mirnaloc/ , by which the user can predict localizations of miRNAs. |
| Description: | Not Available |
| ISSN: | Not Available |
| Type(s) of content: | Research Paper |
| Sponsors: | Not Available |
| Language: | English |
| Name of Journal: | Scientific Reports |
| NAAS Rating: | 10.38 |
| Impact Factor: | 4.99 |
| Volume No.: | 10(1) |
| Page Number: | 1-12 |
| Name of the Division/Regional Station: | Not Available |
| Source, DOI or any other URL: | 10.1038/s41598-020-71381-4 |
| URI: | http://krishi.icar.gov.in/jspui/handle/123456789/73716 |
| Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
There are no files associated with this item.
Items in KRISHI are protected by copyright, with all rights reserved, unless otherwise indicated.