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Related Concept Videos

Proteomics01:33

Proteomics

7.3K
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...
7.3K
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  5. Biomedical And Clinical Sciences
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  9. Predictive And Prognostic Markers
  11. Discrimination Of Etiologically Different Cholestasis By Modeling Proteomics Datasets

Discrimination of Etiologically Different Cholestasis by Modeling Proteomics Datasets

Laura Guerrero1, Jorge Vindel-Alfageme1, Loreto Hierro2

  • 1Centro Nacional de Biotecnología (CNB-CSIC), c/Darwin, 3, 28049 Madrid, Spain.

International Journal of Molecular Sciences
|April 13, 2024

Related Experiment Videos

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
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TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis

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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis

Published on: July 11, 2014

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Quantitative Analysis of Chromatin Proteomes in Disease
08:11

Quantitative Analysis of Chromatin Proteomes in Disease

Published on: December 28, 2012

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View abstract on PubMed

Summary
This summary is machine-generated.

This study used proteomics and machine learning to identify key proteins in cholestasis (disrupted bile flow). A panel of 20 proteins can now accurately distinguish between different types of cholestasis for personalized treatment.

Area of Science:

  • Hepatology
  • Proteomics
  • Bioinformatics

Background:

  • Cholestasis, characterized by impaired bile flow, presents diverse etiologies and symptoms.
  • Accurate patient stratification is crucial for developing targeted therapies for cholestasis.
  • Understanding the molecular basis of cholestasis progression is essential for improving patient care.

Purpose of the Study:

  • To analyze the liver proteome of cholestatic patients to identify molecular differences.
  • To develop a method for stratifying cholestasis patients based on proteomic profiles.
  • To discover a protein panel capable of distinguishing between different cholestasis types.

Main Methods:

  • Proteomic analysis of liver tissue from cholestatic patients and controls.
  • Identification and quantification of liver proteins.
Keywords:
cholestasislivermachine learningquantitative proteomics

Related Experiment Videos

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
07:44

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis

Published on: June 8, 2020

12.7K
Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
11:25

Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis

Published on: July 11, 2014

33.6K
Quantitative Analysis of Chromatin Proteomes in Disease
08:11

Quantitative Analysis of Chromatin Proteomes in Disease

Published on: December 28, 2012

13.1K
  • Application of machine learning algorithms for patient stratification and biomarker discovery.

    • Main Results:

    • Identified and quantified 7161 proteins, with 263 differentially expressed in cholestasis.
    • Discovered deregulated cellular processes contributing to cholestasis progression.
    • Developed a 20-protein panel using machine learning that accurately segregates different cholestasis types.

    Conclusions:

    • Proteomics combined with machine learning offers insights into cholestasis molecular mechanisms.
    • The identified protein panel can discriminate between various cholestasis etiologies.
    • This approach supports the development of precision medicine for cholestasis treatment.