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Related Experiment Video

Updated: Jun 30, 2026

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules
07:35

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules

Published on: December 16, 2021

MS-BID: a Java package for label-free LC-MS-based comparative proteomic analysis.

Daehee Hwang1, Ning Zhang, Hookeun Lee

  • 1Institute for Systems Biology, Seattle, WA 98103, USA. dhhwang@postech.ac.kr

Bioinformatics (Oxford, England)
|September 23, 2008
PubMed
Summary
This summary is machine-generated.

MS-BID is a computational platform for discovering biomarkers from LC-MS proteomic data. It aids in identifying and selecting peptides that differentiate sample groups.

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Related Experiment Videos

Last Updated: Jun 30, 2026

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules
07:35

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Published on: December 16, 2021

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08:11

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Published on: December 28, 2012

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data
09:29

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

Published on: May 15, 2019

Area of Science:

  • Proteomics
  • Computational Biology
  • Biomarker Discovery

Background:

  • Liquid chromatography-mass spectrometry (LC-MS) is a key technology in comparative proteomics.
  • Biomarker discovery from complex proteomic datasets remains a challenge.

Purpose of the Study:

  • To introduce MS-BID (MS Biomarker Discovery Platform), an integrated computational pipeline.
  • To facilitate biomarker discovery using LC-MS-based comparative proteomic analysis.

Main Methods:

  • The MS-BID platform integrates computational tools for peptide detection.
  • It enables matching of detected peptides across multiple LC-MS datasets.
  • The platform facilitates the selection of peptides that discriminate between sample classes.

Main Results:

  • MS-BID provides a structured approach to analyze LC-MS proteomic data.
  • The pipeline supports the identification of potential protein biomarkers.

Conclusions:

  • MS-BID is a valuable computational resource for biomarker discovery in comparative proteomics.
  • The platform streamlines the analysis of LC-MS data for identifying differentiating peptides.