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Related Concept Videos

Proteomics01:33

Proteomics

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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...
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Peptide Identification Using Tandem Mass Spectrometry01:33

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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...
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Related Experiment Video

Updated: Nov 5, 2025

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames
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PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics.

Muhammad Farhan Khalid1, Kanzal Iman1, Amna Ghafoor1

  • 1Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan.

Nucleic Acids Research
|May 17, 2021
PubMed
Summary

PERCEPTRON is a new web platform for top-down proteomics (TDP) that enhances proteoform identification and characterization. This tool significantly improves protein reporting and reduces runtime compared to existing software.

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Area of Science:

  • Proteomics
  • Computational Biology
  • Bioinformatics

Background:

  • Top-down proteomics (TDP) is crucial for characterizing intact proteins and their modifications.
  • Existing TDP software often faces limitations in speed and accuracy for comprehensive proteoform analysis.

Purpose of the Study:

  • To introduce PERCEPTRON, a novel, freely available web-based platform for advanced proteoform identification and characterization in TDP.
  • To present a comprehensive search pipeline integrating multiple algorithms for enhanced TDP data analysis.

Main Methods:

  • PERCEPTRON utilizes a pipeline with algorithms for mass tuning, de novo sequencing, PTM characterization, and proteoform identification.
  • High-throughput processing is achieved using parallel multi-threading on GPUs with the CUDA framework.
  • An intuitive graphical web interface facilitates parameter setting and result visualization.

Main Results:

  • PERCEPTRON demonstrated superior performance in validated tests on TDP datasets.
  • The platform identified up to 135% more proteins and achieved a 10-fold reduction in runtime compared to other TDP software.
  • Accuracy and performance were rigorously validated against existing tools and datasets.

Conclusions:

  • PERCEPTRON significantly advances the state-of-the-art in TDP search software.
  • The platform offers enhanced capabilities for proteoform identification and characterization.
  • PERCEPTRON is publicly accessible online and its code is available for in-house deployment.