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

Protein Organization01:13

Protein Organization

19.5K
19.5K
Protein Organization01:24

Protein Organization

9.0K
9.0K
Protein Organization01:24

Protein Organization

7.2K
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....
7.2K
Protein Networks02:26

Protein Networks

3.7K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.7K
Protein Networks02:26

Protein Networks

1.8K
1.8K
Protein and Protein Structure02:15

Protein and Protein Structure

71.5K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
71.5K

You might also read

Related Articles

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

Sort by
Same author

Structural and biochemical comparison of the FLVCR and CTL membrane protein families in eukaryotes.

Life science alliance·2026
Same author

Lipids are essential for potassium transport by KdpFABC from E. coli.

bioRxiv : the preprint server for biology·2026
Same author

<i>Grin2b</i> 3'UTR is necessary for synaptic plasticity and spatial learning.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Conduction pathway for potassium through the <i>Escherichia coli</i> pump KdpFABC.

eLife·2025
Same author

Dynamics and structural features of the eEF1A1 and eEF1A2 paralogs.

Nucleic acids research·2025
Same author

Structure of the [Ca]E2P intermediate of Ca<sup>2+</sup>-ATPase 1 from Listeria monocytogenes.

EMBO reports·2025

Related Experiment Video

Updated: May 3, 2026

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.1K

Large scale identification and categorization of protein sequences using structured logistic regression.

Bjørn P Pedersen1, Georgiana Ifrim2, Poul Liboriussen3

  • 1Centre for Membrane Pumps in Cells and Disease - PUMPKIN, Danish National Research Foundation, Aarhus C, Denmark ; Department of Molecular Biology, Aarhus University, Aarhus C, Denmark.

Plos One
|January 28, 2014
PubMed
Summary
This summary is machine-generated.

Structured Logistic Regression (SLR) accurately classifies P-type ATPases, a large family of essential cation pumps. This machine learning tool offers a scalable bioinformatics solution for analyzing millions of protein sequences.

More Related Videos

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

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

Published on: July 14, 2015

9.6K
Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

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

Published on: August 16, 2017

6.8K

Related Experiment Videos

Last Updated: May 3, 2026

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.1K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

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

Published on: July 14, 2015

9.6K
Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

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

Published on: August 16, 2017

6.8K

Area of Science:

  • Bioinformatics
  • Machine Learning
  • Structural Biology

Background:

  • Structured Logistic Regression (SLR) is a novel machine learning method initially developed for text categorization.
  • The increasing volume of protein sequence data necessitates automated classification tools.
  • P-type ATPases, crucial membrane pumps for cation transport, were chosen as a model system.

Purpose of the Study:

  • To develop and validate an automated method for classifying P-type ATPases using SLR.
  • To demonstrate the applicability of SLR to large-scale bioinformatics challenges.
  • To generate biological insights into P-type ATPase distribution and characteristics.

Main Methods:

  • Classification of P-type ATPases into 11 predefined categories using SLR.
  • Analysis of 9.3 million protein sequences from UniProtKB.
  • Application of SLR to 1,123 complete genomes from the Entrez database to study pump distribution.
  • Comparison of SLR performance against Hidden Markov Model approaches.
  • Prediction of membrane topology for identified P-type ATPases.

Main Results:

  • SLR-based classifiers achieved high accuracy and scalability in categorizing P-type ATPases.
  • The study successfully classified a substantial number of P-type ATPases across various organisms.
  • Analysis revealed the distribution patterns of these essential pumps in different biological contexts.

Conclusions:

  • SLR provides an effective tool for large-scale bioinformatics studies, exemplified by P-type ATPase classification.
  • The developed classification system is accurate, scalable, and offers proof-of-concept for SLR in bioinformatics.
  • The findings identify novel P-type ATPases as potential targets for future biochemical and structural research.