mLoc-mRNA: predicting multiple sub-cellular localization of mRNAs using random forest algorithm coupled with feature selection via elastic net

mLoc-mRNA: predicting multiple sub-cellular localization of mRNAs using random forest algorithm coupled with feature selection via elastic net

Background: Localization of messenger RNAs (mRNAs) plays a crucial role in the growth and development of cells. Particularly, it plays a major role in regulating spatio-temporal gene expression. The in situ hybridization is a promising experimental technique used to determine the localization of mRN...

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Bibliographic Details
Main Authors: Meher, P.K (Author), Rai, A. (Author), Rao, A.R (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Bioinformatics
biology
cell nucleus
Cell Nucleus
Computational biology
Computational Biology
Computational methods
Cytology
Decision trees
Endoplasmic reticulum
Experimental techniques
Feature selection
Forecasting
Gene expression
genetics
Growth and development
In-situ hybridization
Location
Machine learning
messenger RNA
Random forest algorithm
Random forests
ribosome
Ribosomes
RNA, Messenger
Statistical modeling
Sub-cellular localization
Subcellular location
Tools and techniques
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