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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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...
MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...
Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
Proteomics01:33

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 proteomics...
Protein Networks02:26

Protein Networks

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,...

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Related Experiment Video

Updated: May 26, 2026

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames
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Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Published on: April 11, 2019

OpenKnowledge for peer-to-peer experimentation in protein identification by MS/MS.

Siu-Wai Leung1, Xueping Quan, Paolo Besana

  • 1School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK. swleung@umac.mo.

Automated Experimentation
|December 24, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces peer ranking in the OpenKnowledge infrastructure for automated scientific experiments. Peer ranking effectively evaluates and identifies dominant bioinformatics services in both simulated and real-world scenarios.

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Published on: November 2, 2021

Area of Science:

  • Bioinformatics and Computational Biology
  • Distributed Systems and Peer-to-Peer Computing
  • Scientific Workflow Automation

Background:

  • Traditional scientific workflow platforms lack performance evaluation for automated experimentation.
  • Peer-to-peer environments enable free sharing of experimental protocols and data.
  • Mechanisms for local peer assessment are crucial in decentralized scientific collaborations.

Purpose of the Study:

  • To implement and demonstrate simple peer ranking within the OpenKnowledge peer-to-peer infrastructure.
  • To evaluate peer performance in automated experimentation using simulated and real-world bioinformatics experiments.
  • To facilitate multi-agent interactions and assess individual peer contributions.

Main Methods:

  • Developed a simulated experiment environment with peer ranking using Lightweight Coordination Calculus (LCC).
  • Integrated MS/MS protein identification services as OpenKnowledge Components (OKCs) for automated execution.
  • Monitored and evaluated peer performance using simple peer ranking algorithms.

Main Results:

  • Simulated peer ranking experiments showed a power-law effect, with a few dominant peers.
  • Real-world experiments utilized LCC interaction models with peptide fragment fingerprinting (PFF) and de novo sequencing peers.
  • MASCOT was identified as a dominant peer based on successful runs, demonstrating novel integration and evaluation of proteomic peers.

Conclusions:

  • The OpenKnowledge infrastructure with peer ranking capability provides an effective evaluative environment for automated experimentation.
  • Peer ranking successfully assessed the performance of individual bioinformatics services in a decentralized setting.
  • This approach supports automated scientific discovery and collaboration in complex research areas like proteomics.