Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Modern Molecular Taxonomy

Modern Molecular Taxonomy

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...

Single Nucleotide Polymorphisms-SNPs

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

You might also read

Related Articles

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

Sort by

Same author

Automated implementation of the SwabSeq COVID-19 diagnostic assay on the opentrons flex liquid-handling robot.

Diagnostic microbiology and infectious disease·2026

Same author

Single-cell profiling of DNA methylation in autism spectrum disorder prefrontal cortex reveals distinct regulatory and aging signatures.

Cell genomics·2026

Same author

Leveraging tumor dynamics to discover mutations influencing progression and treatment response for precision oncology.

Genome medicine·2026

Same author

FastGxC: Fast and powerful context-specific eQTL mapping in bulk and single-cell data.

Cell genomics·2026

Same author

Systematic evaluation of 24 extraction and library preparation combinations for metagenomic sequencing of SARS-CoV-2 in saliva.

bioRxiv : the preprint server for biology·2026

Same author

Context-specific genetic effects inform endotypes and treatment in asthma.

The Journal of allergy and clinical immunology·2026

Same journal

Real-time EEG-based epileptic seizure prediction using artificial intelligence: A systematic review.

Artificial intelligence in medicine·2026

Same journal

R-peak detection and ECG data compression scheme based on empirical mode decomposition and wavelet transform.

Artificial intelligence in medicine·2026

Same journal

CastNet: A three-channel EEG-based deep learning model for cross-subject depression detection.

Artificial intelligence in medicine·2026

Same journal

State-of-the-art TinyML approaches for colorectal cancer detection: Current advances, challenges, and future directions.

Artificial intelligence in medicine·2026

Same journal

JRadiEvo: A Japanese radiology report generation model enhanced by evolutionary optimization of model merging.

Artificial intelligence in medicine·2026

Same journal

Causally-informed deep learning towards explainable and generalizable outcome prediction in critical care.

Artificial intelligence in medicine·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 10, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Multi-marker tagging single nucleotide polymorphism selection using estimation of distribution algorithms.

Roberto Santana¹, Alexander Mendiburu, Noah Zaitlen

¹Faculty of Informatics, Universidad Politécnica de Madrid, R. 3306, Campus de Montegancedo, 28660 Boadilla del Monte, Madrid, Spain. roberto.santana@upm.es

Artificial Intelligence in Medicine

|July 24, 2010

Summary

This summary is machine-generated.

This study introduces an optimization algorithm for selecting minimal tagging single nucleotide polymorphism (SNP) sets. The new method significantly reduces the number of SNPs needed compared to existing approaches.

More Related Videos

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene

A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene

Published on: April 1, 2019

Related Experiment Videos

Last Updated: Jun 10, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene

A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene

Published on: April 1, 2019

Area of Science:

Genetics
Bioinformatics
Computational Biology

Background:

Tagging single nucleotide polymorphisms (SNPs) are crucial for genome-wide association studies (GWAS).
Selecting a minimal set of tagging SNPs (tagSNPs) reduces genotyping costs and data complexity.
Existing methods for tagSNP selection may not always yield the most minimal sets.

Purpose of the Study:

To develop and evaluate an optimization algorithm for the automatic selection of a minimal subset of tagging SNPs.
To address the tagSNP selection problem as an optimization task solvable by an Estimation of Distribution Algorithm (EDA).

Main Methods:

The problem of identifying minimal tagSNP sets is framed as an optimization problem.
An Estimation of Distribution Algorithm (EDA) is employed, leveraging SNP correlations to model interactions.
The EDA stochastically searches the solution space and is evaluated using HapMap reference panel data.

Main Results:

The EDA was compared against a SAT solver and the Tagger program.
The EDA achieved a reduction of 10% to 43% in the number of tagging SNPs compared to other algorithms.
The algorithm successfully identified minimal multi-marker tagSNP sets.

Conclusions:

The developed algorithm is effective in identifying minimal multi-marker SNP sets.
This approach significantly reduces the dimensionality of the tagSNP set compared to single-marker sets.
The EDA framework can be adapted for other SNP-related optimization problems.