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

Proteomics01:33

Proteomics

7.6K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.6K
Protein Networks02:26

Protein Networks

4.0K
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,...
4.0K
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

6.6K
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...
6.6K

You might also read

Related Articles

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

Sort by
Same author

Clinical Manifestations.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Public Health.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Cardiovascular rate pressure product is associated with NfL in older adults at risk for AD.

Alzheimer's & dementia (Amsterdam, Netherlands)·2025
Same author

Nutritional Factors and Therapeutic Interventions in Autism Spectrum Disorder: A Narrative Review.

Children (Basel, Switzerland)·2025
Same author

Intake of Table Sugar and Their Corresponding Food Sources in Adults from the 2017-2018 Brazilian National Dietary Survey.

Nutrients·2024
Same author

Human Nutrition Research in the Data Era: Results of 11 Reports on the Effects of a Multiple-Micronutrient-Intervention Study.

Nutrients·2024

Related Experiment Video

Updated: Aug 13, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.2K

Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading.

Jacqueline Pontes Monteiro1, Melissa J Morine2, Fabio V Ued1

  • 1Department of Pediatrics, Ribeirão Preto Medical School, University of São Paulo, Bandeirantes Avenue, 3900, Ribeirão Preto 14049-900, Brazil.

Nutrients
|January 21, 2023
PubMed
Summary
This summary is machine-generated.

Understanding how nutrition impacts disease requires analyzing proteomic data. This study used machine reading to cluster research on nutrition, diet, and proteomics, revealing key thematic areas in human health research.

Keywords:
artificial intelligencediet proteomicsfood proteomicsmachine readingnutriproteomicsnutrition proteomicstransformer-based language model

More Related Videos

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
09:00

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

764
Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

12.0K

Related Experiment Videos

Last Updated: Aug 13, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.2K
A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
09:00

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Published on: April 18, 2025

764
Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

12.0K

Area of Science:

  • Nutritional Science
  • Proteomics
  • Bioinformatics

Background:

  • Nutrition plays a critical role in early disease development, yet underlying mechanisms are not fully understood.
  • High-throughput proteomic methods offer insights into how nutrients, foods, and diets influence health and disease.
  • A comprehensive understanding of the interplay between nutrition and disease requires advanced data analysis techniques.

Purpose of the Study:

  • To identify and analyze the body of scientific literature concerning proteomics, diet, food, and nutrition in humans.
  • To develop a novel machine reading pipeline for processing and categorizing a large corpus of research.
  • To uncover thematic clusters within the proteomic literature related to nutrition and human health.

Main Methods:

  • A novel machine reading pipeline was developed and implemented.
  • The pipeline processed a large collection of articles and abstracts.
  • The identified proteomic corpus was analyzed using text-mining techniques to create thematic clusters based on word content.

Main Results:

  • The machine reading pipeline successfully identified a significant number of relevant publications.
  • Seven distinct thematic clusters were generated from the proteomic corpus, representing key research areas.
  • Examples of publications from these clusters were described to illustrate the thematic content.

Conclusions:

  • Machine reading pipelines are effective tools for analyzing large scientific literature datasets.
  • The identified thematic clusters provide a structured overview of research at the intersection of nutrition, diet, and human proteomics.
  • This approach facilitates a better understanding of how nutritional factors influence health and disease processes through proteomic mechanisms.