Related Experiment Video
Updated: Aug 2, 2025
13:16
Assessment of DNA Contamination in RNA Samples Based on Ribosomal DNA
Published on: January 22, 2018
21.5K
NCodR: A multi-class support vector machine classification to distinguish non-coding RNAs in Viridiplantae
Chandran Nithin1,2, Sunandan Mukherjee1,3, Jolly Basak4
1Computational Structural Biology Lab, Department of Biotechnology, Indian Institute of Technology, Kharagpur 721302, India.
Quantitative Plant Biology
|April 20, 2023
Summary
This study reveals distinct sequence and structure features for plant non-coding RNAs (ncRNAs). A machine learning model accurately classifies these ncRNAs, aiding gene expression research.
Area of Science:
- Plant molecular biology
- Bioinformatics
- Genomics
Background:
- Non-coding RNAs (ncRNAs) are crucial regulators of gene expression in plants.
- Understanding the diversity of ncRNA classes is essential for deciphering gene regulation mechanisms.
Purpose of the Study:
- To analyze sequence and secondary structure features of seven plant ncRNA classes.
- To develop a computational method for accurate ncRNA classification.
Main Methods:
- Analysis of RNA folding measures including AU content and minimum folding energy.
- Examination of k-mer repeat signatures for different ncRNA classes.
- Training and evaluation of eight machine learning classifiers, including Support Vector Machines (SVM).
Main Results:
- Distinct AU content distribution and overlapping regions were observed across ncRNA classes.
- Similar minimum folding energy indices were found, with exceptions for pre-microRNAs (pre-miRNAs) and long non-coding RNAs (lncRNAs).
- Unique k-mer repeat signatures were identified, except for pre-miRNAs and lncRNAs which showed diffuse patterns.
- SVM with a radial basis function achieved high accuracy (~96% average F1 score) in classifying plant ncRNAs.
Conclusions:
- Sequence and structural attributes effectively differentiate plant ncRNA classes.
- The developed classifier, NCodR, provides a robust tool for ncRNA identification and functional studies.
- This work enhances our understanding of ncRNA diversity and regulatory roles in plants.
Related Concept Videos
03:21RNA-seq
10.2K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.2K
01:29Viruses with RNA Genomes
60
RNA viruses are categorized into positive-strand, negative-strand, or double-stranded groups based on their genomic structure and replication mechanisms. This classification dictates how they exploit host cellular machinery for protein synthesis and replication. Some RNA viruses also utilize reverse transcription as part of their life cycle, further diversifying their replication strategies.Positive-Strand RNA VirusesPositive-strand RNA viruses have genomes that function directly as messenger...
60
02:54Evolutionary Relationships through Genome Comparisons
5.9K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.9K
01:28Methods of Classification and Identification
63
Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
63
01:24Microbial Classification System
54
Classification is the process of organizing organisms into hierarchically inclusive groups based on their phenotypic similarities or evolutionary relationships. A species comprises one or more strains, and closely related species are grouped into genera. Genera are further classified into families, families into orders, orders into classes, and so forth, up to the domain level, which is the broadest taxonomic rank derived from a combination of phenotypic and genotypic data.The nomenclature of...
54
02:39lncRNA - Long Non-coding RNAs
8.7K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
8.7K