Affordable Access

Access to the full text

Benchmarking mass spectrometry based proteomics algorithms using a simulated database

Authors
  • Awan, Muaaz Gul1
  • Awan, Abdullah Gul2
  • Saeed, Fahad3
  • 1 Lawrence Berkeley National Laboratory, Berkeley, CA, USA , Berkeley (United States)
  • 2 University of Engineering & Technology (UET), Lahore, Pakistan , Lahore (Pakistan)
  • 3 Florida International University, Miami, FL, USA , Miami (United States)
Type
Published Article
Journal
Network Modeling Analysis in Health Informatics and Bioinformatics
Publisher
Springer Vienna
Publication Date
Mar 26, 2021
Volume
10
Issue
1
Identifiers
DOI: 10.1007/s13721-021-00298-3
Source
Springer Nature
Keywords
License
Yellow

Abstract

Protein sequencing algorithms process data from a variety of instruments that has been generated under diverse experimental conditions. Currently there is no way to predict the accuracy of an algorithm for a given data set. Most of the published algorithms and associated software has been evaluated on limited number of experimental data sets. However, these performance evaluations do not cover the complete search space the algorithm and the software might encounter in real-world. To this end, we present a database of simulated spectra that can be used to benchmark any spectra to peptide search engine. We demonstrate the usability of this database by bench marking two popular peptide sequencing engines. We show wide variation in the accuracy of peptide deductions and a complete quality profile of a given algorithm can be useful for practitioners and algorithm developers. All benchmarking data is available at https://users.cs.fiu.edu/~fsaeed/Benchmark.html

Report this publication

Statistics

Seen <100 times