Proteomics and System Biology in Cardiovascular Diseases
The amount of experimental biological data obtained in the proteomics field (but not limited) is such that computational approaches are found essential for revealing the complexity of protein interactions.
Accordingly many disciplines such as physics, mathematics, chemistry and informatics come into play and are providing biologists with more powerful tools for analyzing their data.
My research is actually focusing in using new or customized pre-existing data analysis algorithms to provide new insights and differences between healthy cells and cardiovascular diseases related cells.
By using R-statistical package I perform data mining, clusterization and advanced filtering analysis on Mass Spectrometry (MS) data. In specific, the MS experiments (e.g. MS/MS TMT, SILAC et.) performed in our group initially identify and quantify proteins in the treated and non-treated cell lines as a function of time.
Such information are re-directed to the Protein Discovery software which analyses the spectra (with SEQUEST or Mascot algorithms) and provides with the protein intensities, score, peptide protein matches etc. in a tabular format that can be successively processed with statistical computational tools.