Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

RNA-seq03:21

RNA-seq

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 microarray-based...
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific primer.
Since the...
Experimental RNAi02:15

Experimental RNAi

RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
RNA Structure01:23

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
RNA Structure01:19

RNA Structure

The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA) involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three...
RNA Structure01:23

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

SERIPH: A Two-Step Extraction Protocol for Selective Enrichment of Semi-Extractable RNAs.

RNA (New York, N.Y.)·2026
Same author

LinearCapR: linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits.

Bioinformatics (Oxford, England)·2026
Same author

Continuation of anti-tuberculosis therapy after Clostridioides difficile infection: a retrospective cohort study.

Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy·2026
Same author

Haemoptysis Caused by Right Intercostal Artery-To-Pulmonary Artery Fistulas Mimicking Cryptogenic Haemoptysis.

Respirology case reports·2026
Same author

Nationwide Survey of Postmortem CT Imaging Protocols among Facilities in Japan.

The Tohoku journal of experimental medicine·2026
Same author

Cross-species gene redesign leveraging ortholog information and generative modeling.

Nature communications·2026

Related Experiment Video

Updated: Jul 10, 2026

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae
09:12

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Published on: February 27, 2026

Stem kernels for RNA sequence analyses.

Yasubumi Sakakibara1, Kris Popendorf, Nana Ogawa

  • 1Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa 223-8522, Japan. yasu@bio.keio.ac.jp

Journal of Bioinformatics and Computational Biology
|October 13, 2007
PubMed
Summary

A new stem kernel method effectively distinguishes functional RNA sequences and detects noncoding RNA regions. This approach outperforms traditional methods in RNA family discrimination and remote homology detection.

More Related Videos

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis
07:29

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

Published on: May 16, 2020

Related Experiment Videos

Last Updated: Jul 10, 2026

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae
09:12

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Published on: February 27, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis
07:29

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

Published on: May 16, 2020

Area of Science:

  • Computational biology
  • Bioinformatics
  • Genomics

Background:

  • Stochastic context-free grammars model RNA secondary structures but struggle with sequence discrimination.
  • Existing methods lack sufficient accuracy for identifying functional RNA families and noncoding regions within genomes.

Purpose of the Study:

  • To introduce a novel stem kernel function for enhanced discrimination and detection of functional RNA sequences.
  • To improve the identification of RNA families and noncoding RNA regions using Support Vector Machines (SVMs).

Main Methods:

  • Developed a novel stem kernel, an extension of string kernels, to measure RNA sequence similarity based on secondary structures.
  • Incorporated analysis of base pairs, stem structures, and pseudoknots, including those of arbitrary lengths.
  • Utilized dynamic programming for efficient stem kernel calculation and applied SVMs for sequence discrimination.

Main Results:

  • The stem kernel demonstrated strong discrimination ability, outperforming conventional methods in identifying RNA family members.
  • Successfully detected remotely homologous RNA families based on secondary structure similarities.
  • Showcased the potential for discovering novel RNA families within genome sequences.

Conclusions:

  • The stem kernel offers a powerful new tool for RNA sequence analysis and functional RNA detection.
  • This method significantly advances the ability to identify and classify RNA sequences and families.
  • The stem kernel's effectiveness suggests broad applications in genomic research and RNA discovery.