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

12.1K
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...
12.1K
Cluster Sampling Method01:20

Cluster Sampling Method

14.7K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
14.7K
RNA Structure01:23

RNA Structure

79.1K
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...
79.1K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

971
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
971
Ribosomal RNA Synthesis02:53

Ribosomal RNA Synthesis

14.8K
Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
Ribosome biogenesis begins with the synthesis of 5S and 45S pre-rRNAs by distinct RNA polymerases. The primary transcripts are extensively processed and modified before they are bound and folded by ribosomal proteins and assembly factors,...
14.8K
RNA Stability01:53

RNA Stability

35.7K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
35.7K

You might also read

Related Articles

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

Sort by
Same author

<i>Special Issue:</i> 13th International Conference on Computational Advances in Bio and Medical Sciences.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same author

MHASS: Microbiome HiFi Amplicon Sequencing Simulator.

Bioinformatics (Oxford, England)·2025
Same author

First Mitogenome of the Critically Endangered Arabian Leopard (<i>Panthera pardus nimr</i>).

Animals : an open access journal from MDPI·2025
Same author

<i>Special Section:</i> 12th International Computational Advances in Bio and Medical Sciences (ICCABS 2023).

Journal of computational biology : a journal of computational molecular cell biology·2025
Same author

A frameshift-generated cancer neoepitope that controls tumor burden in prophylaxis as well as therapy.

Journal of immunology (Baltimore, Md. : 1950)·2025
Same author

Low-avidity T cells drive endogenous tumor immunity in mice and humans.

Nature immunology·2025

Related Experiment Video

Updated: Feb 3, 2026

Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq
06:22

Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq

Published on: August 25, 2020

13.5K

Single cell RNA-seq data clustering using TF-IDF based methods.

Marmar Moussa1, Ion I Măndoiu2

  • 1University of Connecticut, Storrs, 06269, CT, USA.

BMC Genomics
|October 28, 2018
PubMed
Summary
This summary is machine-generated.

We developed new computational methods for analyzing single-cell RNA sequencing (scRNA-Seq) data. These TF-IDF based approaches improve cell clustering, outperforming existing methods for biological data analysis.

Keywords:
ClusteringSingle cell RNA-SeqTF-IDF

More Related Videos

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.4K
Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

388

Related Experiment Videos

Last Updated: Feb 3, 2026

Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq
06:22

Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq

Published on: August 25, 2020

13.5K
Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.4K
Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

388

Area of Science:

  • Computational Biology
  • Genomics
  • Bioinformatics

Background:

  • Single-cell transcriptomics is essential for studying cellular diversity and discovering new cell types.
  • Advances in single-cell RNA sequencing (scRNA-Seq) necessitate robust clustering algorithms capable of handling noise and large datasets.

Purpose of the Study:

  • To introduce novel computational methods for clustering scRNA-Seq data.
  • To adapt text-mining techniques for biological data analysis.

Main Methods:

  • Utilized the Term Frequency - Inverse Document Frequency (TF-IDF) transformation, a technique from text analysis.
  • Applied TF-IDF to scRNA-Seq data for unsupervised clustering.

Main Results:

  • TF-IDF based methods demonstrate strong performance in clustering scRNA-Seq data.
  • Empirical results confirm the effectiveness of these novel approaches.

Conclusions:

  • TF-IDF methods provide a superior alternative for scRNA-Seq data clustering.
  • These findings advance the analysis of cellular heterogeneity using transcriptomic data.