Difference between revisions of "QuiXoT software package"

From PROTEOMICA
Jump to: navigation, search
(Updated last version)
Line 5: Line 5:
 
'''QuiXoT''' is a bioinformatic software package developed especially to provide a set of tools for quantitative proteomics.
 
'''QuiXoT''' is a bioinformatic software package developed especially to provide a set of tools for quantitative proteomics.
  
The main program of the package is the homonym '''[[QuiXoT]]''', whose latest stable release is QuiXoT 1.4.02.
+
The main program of the package is the homonym '''[[QuiXoT]]''', whose latest stable release is QuiXoT 1.5.00.
  
 
=== Why QuiXoT? ===
 
=== Why QuiXoT? ===

Revision as of 15:18, 3 April 2017

QuiXoT logo.png

What is QuiXoT?

QuiXoT is a bioinformatic software package developed especially to provide a set of tools for quantitative proteomics.

The main program of the package is the homonym QuiXoT, whose latest stable release is QuiXoT 1.5.00.

Why QuiXoT?

The tools available to the scientific community to quantitate and make statistical analyses in large scale quantitative proteomic experiments were very limited. For this reason we started developing QuiXoT in our laboratory.

In 2006 we started developing a tool for 18O isotope-labeling experiments able to automatically extract well assigned spectra, quantitate the data and make a fast statistical analysis. Everything within one hour.

Later, in February 2009, we decided to expand the software in order to analyze any type of isotopic labeling and to accept data from the most common mass-spectrometres.

Who is behind QuiXoT?

QuiXoT has been developed originally by Pedro Navarro and afterwards by Marco Trevisan-Herraz, at the Cardiovascular Proteomics Lab of Prof. Jesús Vázquez, within the Centro Nacional de Investigaciones Cardiovasculares (CNIC), in Madrid, Spain (originally at the Protein Chemistry and Proteomics Lab, in the Centro de Biología Molecular Severo Ochoa, CBM-CSIC).

The QuiXoT logo has been designed by José Pérez Pérez and Pedro Navarro.

References

  • I. Jorge, P. Navarro, P. Martinez-Acedo, et al., «Statistical model to analyze quantitative proteomics data obtained by 18O/16O labeling and linear ion trap mass spectrometry: Application to the study of VEGF-induced angiogenesis in endothelial cells», Mol Cell Proteomics , (2009) (DOI: 10.1074/mcp.M800260-MCP200)
  • P. Navarro, M. Trevisan-Herraz, E. Bonzon-Kulichenko, et al., «General Statistical Framework for Quantitative Proteomics by Stable Isotope Labeling», J Proteome Res , (2014) (DOI: 10.1021/pr4006958)