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Database Search Engines: Paradigms, Challenges and Solutions.

Kenneth Verheggen^1,2, Lennart Martens^1,2, Frode S Berven^3,4,5

¹Department of Medical Protein Research, VIB, Ghent, Belgium.

Advances in Experimental Medicine and Biology

|December 16, 2016

Summary

This summary is machine-generated.

This study introduces database search engines for inferring peptides from mass spectrometry data. It demonstrates using open-source software like SearchGUI to address common challenges in sequence database searching.

Keywords:

Peptide identification Search engines Sequence database searching Shotgun proteomics

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Area of Science:

Proteomics
Bioinformatics
Mass Spectrometry

Background:

Protein identification from mass spectrometry data relies on inferring peptides from tandem mass spectra.
Database search engines are the standard computational tools for this inference process.

Purpose of the Study:

To introduce the fundamental principles of database search engines used in proteomics.
To demonstrate the application of these engines using open-source software and a freely available interface.
To provide guidance on addressing and mitigating issues in sequence database searching.

Main Methods:

Principles of database search engines are explained.
Demonstration of database search engine usage via the SearchGUI interface.
Discussion of common challenges and solutions in sequence database searching.

Main Results:

Understanding of database search engine principles for peptide inference.
Practical skills in using SearchGUI for mass spectrometry data analysis.
Strategies for improving the accuracy and efficiency of protein identification.

Conclusions:

Database search engines are crucial for peptide inference in shotgun proteomics.
Open-source tools like SearchGUI facilitate accessible and effective data analysis.
Addressing search-related issues enhances the reliability of protein identification from mass spectrometry data.