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

You might also read

Related Articles

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

Sort by

Same author

CD4/CD8 ratio is associated with structural reorganization of vaccine-induced immune responses in people living with HIV.

Frontiers in immunology·2026

Same author

An in vivo fitness gene of Toxoplasma, MIC11, is essential for PLP1-mediated egress from host cells.

Nature communications·2026

Same author

Human DHX29 detects nonoptimal codon usage to regulate mRNA stability.

Science (New York, N.Y.)·2026

Same author

Regnase-1-mediated regulation of neutrophils modulates SARS-CoV-2 pneumonia.

PLoS pathogens·2026

Same author

Stratification of immunotherapy responses by adaptive immune receptor repertoires.

Trends in molecular medicine·2026

Same author

From benchmarking alignment of genome assemblies to IMGT annotation: the paradigm of the bovine Bos taurus T cell receptor (TRG) locus.

BMC genomics·2025

Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026

Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026

Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026

Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026

Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026

Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 21, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A simple method to control over-alignment in the MAFFT multiple sequence alignment program.

Kazutaka Katoh¹, Daron M Standley²

¹Immunology Frontier Research Center, Osaka University, Suita 565-0871, Japan.

Bioinformatics (Oxford, England)

|May 7, 2016

Summary

This summary is machine-generated.

MAFFT now features a new method to prevent over-alignment in multiple sequence alignments. This approach uses a variable scoring matrix to improve accuracy, especially with noisy sequence data.

More Related Videos

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Related Experiment Videos

Last Updated: Mar 21, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Increasingly noisy protein sequence data, due to sequencing errors and gene prediction challenges, elevates the risk of over-alignment in multiple sequence alignment (MSA).
Conventional MAFFT, while sensitive to conserved regions in remote homologs, faces challenges with low-quality sequences.

Purpose of the Study:

To introduce a novel feature in MAFFT designed to suppress over-alignment.
To enhance the accuracy of multiple sequence alignments, particularly when dealing with imperfect sequence data.

Main Methods:

Implementation of a variable scoring matrix within the MAFFT algorithm.
The scoring matrix adapts dynamically based on the global similarity between sequence pairs or groups during alignment.

Main Results:

The new method significantly increases the number of correctly placed gaps in both simulated and real datasets.
While slightly decreasing sensitivity on real protein benchmarks, the method shows a neutral effect on sensitivity in simulations.
The approach is biologically plausible and compatible with dynamic programming-based MSA methods.

Conclusions:

The new MAFFT feature effectively mitigates over-alignment issues caused by noisy sequence data.
This advancement improves the reliability of multiple sequence alignments for biological sequence analysis.