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

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

6.2K
Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
6.2K
Classification of Systems-II01:31

Classification of Systems-II

638
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
638
Classification of Systems-I01:26

Classification of Systems-I

725
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
725
Classification of Signals01:30

Classification of Signals

1.5K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.5K
Stereotype Content Model02:16

Stereotype Content Model

13.0K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
13.0K
Force Classification01:22

Force Classification

2.8K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
2.8K

You might also read

Related Articles

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

Sort by
Same author

Tuning Sulfur Reduction via Unique Radical-Mediated Solid-Liquid-Solid Pathway for High-Rate Aqueous Zn-S Batteries.

Nano letters·2026
Same author

Knockout of bsal/cel.2 results in growth retardation, reduced lipid digestion and altered energy metabolism in medaka larvae (oryzias latipes).

Functional & integrative genomics·2026
Same author

Training-Free Open-Set Domain Adaptation With Vision-Language Models.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

DreamAssemble: Complex Multi-Object Text-to-3D Generation via Multi-Density Neural Fields.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Public acceptance of LLM-driven healthcare chatbots in China: An empirical study.

Digital health·2026
Same author

Recovery of soluble white proteins from discarded brown juice of lucerne biorefinery by integrating foam separation and aqueous two-phase extraction.

Preparative biochemistry & biotechnology·2026
Same journal

Correction to "Mathematical Modelling of COVID-19 Transmission in Kenya: A Model with Reinfection Transmission Mechanism".

Computational and mathematical methods in medicine·2025
Same journal

RETRACTION: Ligustrazine Inhibits Lung Phosphodiesterase Activity in a Rat Model of Allergic Asthma.

Computational and mathematical methods in medicine·2025
Same journal

RETRACTION: Delivery of miR-224-5p by Exosomes from Cancer-Associated Fibroblasts Potentiates Progression of Clear Cell Renal Cell Carcinoma.

Computational and mathematical methods in medicine·2025
Same journal

RETRACTION: Empirical Analysis of the Nursing Effect of Intelligent Medical Internet of Things in Postoperative Osteoarthritis.

Computational and mathematical methods in medicine·2025
Same journal

RETRACTION: Evaluation and Analysis of the Intervention Effect of Systematic Parent Training Based on Computational Intelligence on Child Autism.

Computational and mathematical methods in medicine·2024
Same journal

RETRACTION: Humanistic Spirit Training of Medical Students Based on Multisource Medical Data Fusion.

Computational and mathematical methods in medicine·2024
See all related articles

Related Experiment Video

Updated: Apr 23, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.0K

A method of protein model classification and retrieval using bag-of-visual-features.

Jinlin Ma1, Ziping Ma2, Baosheng Kang3

  • 1School of Information and Technology, Northwest University, Xi'an 710120, China ; School of Mathematics and Information Science, North University of Nationalities, Yinchuan 750021, China.

Computational and Mathematical Methods in Medicine
|September 27, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a new visual method for protein classification and retrieval by analyzing protein images. The approach uses image features to measure visual similarity, outperforming existing methods in retrieval and categorization tasks.

Related Experiment Videos

Last Updated: Apr 23, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.0K

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Computer Vision

Background:

  • Protein structure classification and retrieval are crucial for understanding protein function and evolution.
  • Conventional methods often rely on sequence or structural alignment, which can be computationally intensive or miss subtle similarities.
  • A visual approach offers a novel perspective for analyzing and comparing protein models.

Purpose of the Study:

  • To develop and evaluate a novel visual method for protein model classification and retrieval.
  • To leverage image feature extraction for measuring visual similarity between protein structures.
  • To compare the proposed method's performance against existing techniques.

Main Methods:

  • Generating multiview images of protein models using an octahedron surrounding the protein.
  • Extracting local image features using the Speeded Up Robust Features (SURF) algorithm.
  • Vector quantization of local features into a visual codebook to create visual words.
  • Calculating similarity distances between protein feature vectors using Kullback-Leibler Divergence (KLD).

Main Results:

  • The proposed visual method demonstrates effective protein model classification and retrieval.
  • Experimental results indicate encouraging performance compared to other established methods.
  • The approach successfully captures visual similarities for categorization and retrieval tasks.

Conclusions:

  • The novel visual method provides an effective alternative for protein model analysis.
  • Image feature extraction and visual similarity measurement offer a promising direction for protein research.
  • This technique enhances capabilities in protein retrieval and categorization within structural bioinformatics.