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

Proteomics

Proteomics

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...

You might also read

Related Articles

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

Sort by

Same author

Hypermobility and chronic pain in adolescents: diverging functional and neural profiles without sensory differences.

Pain·2026

Same author

AI Guided Parenteral Nutrition Therapy After Hematopoietic Stem Cell Transplantation.

NPJ digital medicine·2026

Same author

Systemic immune dysregulation in hypertensive disorders of pregnancy persists years after delivery.

Frontiers in immunology·2026

Same author

A machine learning model for frailty based on wearable device measurements.

Communications medicine·2026

Same author

Preoperative lymphocyte signature predicts pancreatic fistula after pancreatoduodenectomy.

Communications medicine·2026

Same author

Early gestational prediction of spontaneous preterm birth using a validated three-protein serum biomarker panel.

BMC medicine·2026

Same journal

Breathing Physiology into the Art of Neonatal Respiratory Care.

Clinics in perinatology·2026

Same journal

The Science and Art of Neonatal Respiratory Care.

Clinics in perinatology·2026

Same journal

Ex Utero Artificial Womb Support: Promising Future for Extremely Preterm Infants.

Clinics in perinatology·2026

Same journal

Advances in the Use of Cell-Based Therapies for Prevention of Bronchopulmonary Dysplasia.

Clinics in perinatology·2026

Same journal

Evaluation and Management of Genetic Respiratory Disorders Presenting as Hypoxemic Respiratory Failure in the Newborn Infant.

Clinics in perinatology·2026

Same journal

Modern Surfactant Delivery Methods with a Focus on Implementation of Surfactant Administration Through Laryngeal and Supraglottic Airways.

Clinics in perinatology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 27, 2025

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing Frog Embryo

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing Frog Embryo

Published on: April 21, 2022

Predicting Preterm Birth Using Proteomics.

Ivana Marić¹, David K Stevenson¹, Nima Aghaeepour²

¹Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 453 Quarry Road, Palo Alto, CA 94304, USA.

Clinics in Perinatology

|May 5, 2024

Summary

This summary is machine-generated.

Predicting spontaneous preterm birth (PTB) and preeclampsia is challenging. This review explores proteomics signatures and composite biomarkers to improve PTB risk prediction for better maternal and infant outcomes.

Keywords:

Biomarkers Biosignatures Composite signatures Computation Multiomics Omics Preeclampsia Proteome

More Related Videos

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

Published on: October 20, 2016

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Published on: August 28, 2021

Related Experiment Videos

Last Updated: Jun 27, 2025

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing Frog Embryo

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing Frog Embryo

Published on: April 21, 2022

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

Published on: October 20, 2016

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Published on: August 28, 2021

Area of Science:

Reproductive biology and obstetrics.
Biomarker discovery and proteomics.
Clinical prediction modeling.

Background:

Preterm birth (PTB) presents complex challenges due to diverse causes and risk factors.
Accurate prediction of PTB, spontaneous or medically indicated, remains a significant clinical hurdle.
Preeclampsia is a major complication often leading to medically indicated PTB.

Purpose of the Study:

To review the discovery of proteomics signatures for predicting spontaneous PTB and preeclampsia.
To identify potential proteomics biomarker candidates for PTB risk assessment.
To discuss obstacles in developing clinically accurate biomarkers and explore composite signatures.

Main Methods:

Proteomics analysis techniques are described.
Review of identified proteomics biomarker candidates.
Methods for deriving composite signatures combining proteomics and clinical data are discussed.

Main Results:

Several proteomics biomarker candidates for PTB and preeclampsia prediction have been identified.
Obstacles to clinical implementation of proteomics biomarkers are outlined.
Composite signatures show potential for increased predictive power.

Conclusions:

Proteomics holds promise for identifying biomarkers to predict spontaneous PTB and preeclampsia.
Overcoming current obstacles is crucial for clinical translation of these biomarkers.
Integrating clinical parameters with proteomics data may enhance predictive accuracy for PTB risk.