Attila Kertesz-Farkas Made a Report "Data mining problems in computational mass spectrometry"

November 11, Attila Kertesz-Farkas, Associate Professor, Faculty of Computer Science, School of Data Analysis and Artificial Intelligence, gave a talk at a seminar of International Laboratory for Intelligent Systems and Structural Analysis.

Tandem mass spectrometry has been extensively used to determine the amino acid sequence of a protein molecule. Amino acids are the building blocks of protein molecules, traditionally, there are 20 of them, and knowing the amino acid sequences of proteins gives us important insight to the function and structure of the protein molecule.
A protein first in vitro has been cut into smaller pieces, called peptides, to avoid experimental complexity. A mass spectrometer is then used to measure the mass distribution (spectrum) of the peptide fragments. These spectra, generated, can be considered as fingerprint of the peptide molecule. Computational programs are then applied to identify the amino acid sequence of proteins from mass spectrum data.
In this presentation, I gave a general introduction to the computational challenges that scientist faces every day in mass spectrometry data analysis.