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

Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

354
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
354
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

299
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
299
MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

6.1K
Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.
Matrix-assisted laser desorption ionization (MALDI) is a commonly...
6.1K
Microorganisms in Medicine and Therapeutics01:29

Microorganisms in Medicine and Therapeutics

641
Microorganisms play a fundamental role in vaccine development, gene therapy, and therapeutic production. Their biological properties are harnessed to advance medicine and public health. Beyond immunization, microorganisms contribute to gut health, antibiotic synthesis, and genetic disease treatment.Live Attenuated and Inactivated VaccinesLive attenuated vaccines, such as the measles, mumps, and rubella (MMR) vaccine, utilize weakened forms of pathogens to closely resemble natural infections.
641
Key Techniques in Microbiology01:29

Key Techniques in Microbiology

1.1K
Aseptic techniques prevent contamination, ensure experimental accuracy, and protect researchers and microbial cultures. These techniques are essential in clinical, industrial, and research settings where sterility is required.Maintaining Sterility in Laboratory PracticesScientists maintain sterility by sterilizing tools with heat or chemicals, disinfecting work surfaces, and handling cultures in controlled environments. Working near an open flame or within a laminar flow hood reduces the risk...
1.1K
Methods of Classification and Identification01:28

Methods of Classification and Identification

612
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...
612

You might also read

Related Articles

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

Sort by
Same author

Cork-polypropylene composites for food contact: a comprehensive study of morphology, migration, chemical safety, and sensory analysis.

Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment·2026
Same author

Correction to: Global 30-Day Morbidity and Mortality of Primary Bariatric Surgery Combined with Another Procedure: The BLEND Study.

Obesity surgery·2026
Same author

Deciphering the role of adipose tissue microbial DNA in obesity-related metabolic dysfunction.

The Journal of clinical endocrinology and metabolism·2026
Same author

Stromal and endothelial transcriptional changes during progression from MGUS to myeloma and after treatment response.

Nature communications·2026
Same author

Synthesis, characterization, and application of magnetic novel nanofiber membranes for the removal of heavy-metal, organic and biological pollutants from wastewater.

RSC advances·2026
Same author

Prolonged Inflammation Associates With Greater Infarct Size and Poor Outcome After ST-Segment Elevation Myocardial Infarction.

JACC. Basic to translational science·2026

Related Experiment Video

Updated: Nov 14, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

30.6K

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions.

Isabel Moreno-Indias1,2, Leo Lahti3, Miroslava Nedyalkova4

  • 1Instituto de Investigación Biomédica de Málaga (IBIMA), Unidad de Gestión Clìnica de Endocrinologìa y Nutrición, Hospital Clìnico Universitario Virgen de la Victoria, Universidad de Málaga, Málaga, Spain.

Frontiers in Microbiology
|March 11, 2021
PubMed
Summary

The human microbiome is a key research area, generating complex data that requires advanced statistical and machine learning methods. New techniques are essential for analyzing this heterogeneous data and ensuring reproducible results in microbiome studies.

Keywords:
ML4Microbiomebiomarker identificationmachine learningmicrobiomepersonalized medicine

More Related Videos

A Method for Targeted 16S Sequencing of Human Milk Samples
09:09

A Method for Targeted 16S Sequencing of Human Milk Samples

Published on: March 23, 2018

10.1K
Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
07:21

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Published on: August 25, 2018

13.2K

Related Experiment Videos

Last Updated: Nov 14, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

30.6K
A Method for Targeted 16S Sequencing of Human Milk Samples
09:09

A Method for Targeted 16S Sequencing of Human Milk Samples

Published on: March 23, 2018

10.1K
Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
07:21

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Published on: August 25, 2018

13.2K

Area of Science:

  • Human biology and biomedicine
  • Microbiome research
  • Statistical and machine learning applications

Background:

  • The human microbiome is a significant area of research in biology and medicine.
  • Microbiome studies produce high-throughput omics data with inherent heterogeneity and variability.
  • Analyzing this complex data presents statistical and machine learning challenges.

Purpose of the Study:

  • To review and discuss emerging statistical and machine learning applications in human microbiome research.
  • To introduce the COST Action CA18131 "ML4Microbiome" initiative.
  • To highlight the need for new techniques to address data heterogeneity and emerging applications.

Main Methods:

  • Review of statistical and machine learning techniques applied to microbiome data.
  • Discussion of challenges in study design, data processing, standardization, and analysis.
  • Introduction of a collaborative initiative (ML4Microbiome) for advancing the field.

Main Results:

  • Identification of broad statistical and machine learning challenges in microbiome research.
  • Recognition of the need for novel techniques to handle data heterogeneity and new applications.
  • Establishment of a collaborative network to address standardization, benchmarking, and tool development.

Conclusions:

  • Advanced statistical and machine learning methods are crucial for interpreting complex human microbiome data.
  • Standardization of analysis pipelines and development of new tools are essential for reproducibility.
  • Collaborative efforts like ML4Microbiome are vital for addressing current and future challenges in microbiome research.