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

Protein Complex Assembly

Protein Complex Assembly

Protein Complex Assembly

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types. Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...

Multi-species Conserved Sequences

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...

Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...

Protein and Protein Structures

Protein and Protein Structures

Protein Networks

Protein Networks

You might also read

Related Articles

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

Sort by

Same author

FBApro: A fast, simple linear transformation for diverse metabolic modeling tasks.

ArXiv·2026

Same author

Single-cell transcriptomics reveals FXR1 as an actionable target for siRNA therapy in ovarian cancer.

Nature communications·2026

Same author

Preface.

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

Same author

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): the interplay of gut microbiome, insulin resistance, and diabetes.

Frontiers in medicine·2025

Same author

eIF4E Enriched Extracellular Vesicles Induce Immunosuppressive Macrophages through HMGCR-Mediated Metabolic Rewiring.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025

Same author

Locality-aware pooling enhances protein language model performance across varied applications.

Bioinformatics (Oxford, England)·2025

Search research articles

Related Experiment Video

Updated: Apr 11, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Fast, accurate construction of multiple sequence alignments from protein language embeddings.

Minh Hoang¹, Isabel Armour-Garb^1,2, Mona Singh^1,2

¹Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.

Biorxiv : the Preprint Server for Biology

|April 10, 2026

Summary

We introduce ARIES, a novel method for multiple sequence alignment (MSA) using protein language models (PLMs). ARIES significantly improves alignment accuracy, especially for low-similarity sequences, outperforming traditional methods.

Keywords:

Deep Learning Multiple Sequence Alignment Protein Language Model

More Related Videos

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Related Experiment Videos

Last Updated: Apr 11, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Area of Science:

Computational biology
Bioinformatics
Genomics

Background:

Multiple sequence alignment (MSA) is crucial for understanding protein function and evolution.
Traditional MSA methods struggle with low-sequence identity, often called the "twilight zone."
Protein Language Models (PLMs) offer a new way to capture evolutionary and contextual information.

Purpose of the Study:

To develop a new MSA algorithm leveraging PLM embeddings.
To improve MSA accuracy and scalability, particularly in low-identity regimes.
To demonstrate the effectiveness of PLMs in comparative sequence analysis.

Main Methods:

Generated amino acid embeddings using PLMs.
Developed a windowed reciprocal-weighted embedding similarity metric.
Created the ARIES algorithm using PLM embeddings and dynamic time warping for global MSA construction.

Main Results:

ARIES achieved higher accuracy than state-of-the-art methods on diverse benchmark datasets.
The method showed particular strength in low-identity alignment scenarios.
ARIES demonstrated near-linear scalability with an increasing number of sequences.

Conclusions:

PLMs can significantly enhance MSA accuracy and scalability.
ARIES represents a breakthrough in applying PLMs to comparative sequence analysis.
This approach has the potential to transform the field of computational biology.