Rapid development of Proteomic applications with the AIBench framework

J Integr Bioinform. 2011 Sep 15;8(3):171. doi: 10.2390/biecoll-jib-2011-171.


In this paper we present two case studies of Proteomics applications development using the AIBench framework, a Java desktop application framework mainly focused in scientific software development. The applications presented in this work are Decision Peptide-Driven, for rapid and accurate protein quantification, and Bacterial Identification, for Tuberculosis biomarker search and diagnosis. Both tools work with mass spectrometry data, specifically with MALDI-TOF spectra, minimizing the time required to process and analyze the experimental data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacteria / chemistry
  • Bacteria / genetics
  • Bacteria / metabolism*
  • Bacterial Proteins / chemistry
  • Bacterial Proteins / genetics
  • Bacterial Proteins / metabolism*
  • Biomarkers / chemistry
  • Biomarkers / metabolism
  • Proteomics / instrumentation*
  • Proteomics / methods*
  • Software*
  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / methods
  • Tuberculosis / genetics
  • Tuberculosis / metabolism*


  • Bacterial Proteins
  • Biomarkers