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 Organization

Protein Organization

Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

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...

Conservation of Protein Domains

Conservation of Protein Domains

Proteins: From Genes to Degradation

Proteins: From Genes to Degradation

Within a biological system, the DNA encodes the RNA, and the nucleotide sequence in the RNA further defines the amino acid sequence in the protein. This is referred to as “The Central Dogma of Molecular Biology” - a term coined by Francis Crick. Central dogma is a firm principle in biology that defines the flow of genetic information within any life form. The two fundamental steps in central dogma are - transcription and translation.
Transcription is the synthesis of RNA...

Proteins: From Genes to Degradation

Proteins: From Genes to Degradation

You might also read

Related Articles

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

Sort by

Same author

Peripheral blood immune profiling reveals key signatures in newly diagnosed NK/T cell lymphoma patients.

Theranostics·2026

Same author

Prediction of Antipsychotic Drug Doses for BPSD in Alzheimer's Disease Using Deep Learning Techniques.

Diagnostics (Basel, Switzerland)·2026

Same author

Mediterranean diet adherence and dietary fat intake in relation to lung cancer outcomes: a prospective cohort study.

Food & function·2026

Same author

Evaluating DNA Function Understanding in Genomic Language Models Using Evolutionarily Implausible Sequences.

ACS synthetic biology·2026

Same author

Structural motif search across the protein universe with Folddisco.

Nature biotechnology·2026

Same author

Accurate protein stability prediction for small domains using mega-scale experiments.

bioRxiv : the preprint server for biology·2026

Same journal

Prime editing for precise genome engineering and modulation of fungal metabolism.

Nature biotechnology·2026

Same journal

Retargeted serine integrases for one-step, precise integration of large DNA sequences in human cells.

Nature biotechnology·2026

Same journal

A retargeted recombinase for precise insertion of large DNA.

Nature biotechnology·2026

Same journal

Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles.

Nature biotechnology·2026

Same journal

Spatially resolved profiling of extracellular vesicles in tissues with Spatial-EV-seq.

Nature biotechnology·2026

Same journal

Mapping the spatial landscape of extracellular vesicles in tissues with Spatial-EV-seq.

Nature biotechnology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 14, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Democratizing protein language model training, sharing and collaboration.

Jin Su^1,2, Zhikai Li², Tianli Tao²

¹Zhejiang University, Hangzhou, China.

Nature Biotechnology

|October 24, 2025

Summary

This summary is machine-generated.

Researchers can now train and deploy protein language models without deep machine learning expertise using the new SaprotHub platform. This framework enables collaborative model building and sharing for diverse protein applications.

More Related Videos

Escherichia coli-Based Cell-Free Protein Synthesis: Protocols for a robust, flexible, and accessible platform technology

Escherichia coli-Based Cell-Free Protein Synthesis: Protocols for a robust, flexible, and accessible platform technology

Published on: February 25, 2019

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Related Experiment Videos

Last Updated: Jan 14, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Escherichia coli-Based Cell-Free Protein Synthesis: Protocols for a robust, flexible, and accessible platform technology

Escherichia coli-Based Cell-Free Protein Synthesis: Protocols for a robust, flexible, and accessible platform technology

Published on: February 25, 2019

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Area of Science:

Computational Biology
Bioinformatics
Machine Learning

Background:

Training large-scale protein language models demands specialized machine learning expertise, limiting accessibility for many researchers.
Existing platforms may lack intuitive interfaces for model training, prediction, and management.

Purpose of the Study:

To introduce SaprotHub, an accessible platform for training and deploying protein language models.
To enable researchers without deep machine learning backgrounds to utilize and contribute to protein model development.
To facilitate collaborative building, storage, and sharing of customized protein models.

Main Methods:

Development of the SaprotHub platform, featuring an intuitive user interface.
Integration with Google Colab to create the ColabSaprot framework.
Enabling functionalities for model training, prediction, storage, and sharing.

Main Results:

SaprotHub lowers the barrier to entry for protein language model development.
The ColabSaprot framework supports a wide range of protein-related training and prediction tasks.
Facilitates collaborative model creation and dissemination among researchers.

Conclusions:

SaprotHub democratizes access to advanced protein language modeling tools.
The platform fosters collaboration and accelerates research in protein science.
Enables the development of customized models for specific research needs.