I am interested in the development and application of methods in the field of systems biology. For this purpose I have helped in the development of functional modularization approaches  or have applied complex clustering methods to gene expression data . However this does not limit the interest in the biological aspect. Analysis of a wound healing experiment on the chicken chorio-allantoic membrane (CAM)  intrigued me to explore and analyse the inflammatory response associated to rheumatoid (RA) and osteoarthritis (OA). The difference between these two diseases is the chronic systemic inflammation that occurs in the synovial joints of patients with RA. OA on the other hand is usually not accompanied by inflammation although the destruction of the articular cartilage is common between the two. We were interested to see how the fibroblasts of these two diseases react to stimulation by serum, a commonly used additive in in-vitro experiments. My analysis showed that synovial fibroblasts derived from OA and RA grown in high serum are almost indistinguishable. In addition we have also identified a down regulation of integrin-beta 3 (ITGB3) by patients with RA. We are currently compiling the manuscript for publication.
Another interest lies in the modelling of cell to cell communication. To this extend I am currently creating a dataset using Agilent Gene Expression Arrays of an in-vitro timecourse of a ‘normal’ prostate cancer cell line (RWPE1) grown in the presence of a prostate cancer cell line (DU145). The idea here is to be able to model the interaction between the two cell lines and understand the importance of factors secreted by either cell. Preliminary results showed an interesting up regulation of splicing factors with associated up regulation of mRNA splicing, however we need to perform further experiments to show statistical significance.
In contrast to the previously described projects I have also developed a method that correlates chemical structure to gene expression data summarized in functional modules with the use of the KEGG database . For this particular analysis we have used public domain data, created by iconix using in-vivo experiments on rats, and we are currently working to create our own dataset but using daphnia magna as the species. This would allow an integration into environmental toxicology and development of further models based on a common species used in assessing chemical toxicity.
 K. Sameith, P. Antczak, E. Marston, N. Turan, D. Maier, T. Stankovic, F. Falciani. Functional modules integrating essential cellular functions are predictive of the response of leukaemia cells to DNA damage. Bioinformatics 24(22): 2602-2607. Nov 2008.
 N.A. Burton, M.D. Johnson, P. Antczak, A. Robinson and P.A. Lund. Novel aspects of the acid response network of E. coli K-12 are revealed by a study of transcriptional dynamics. Journal of Molecular Biology 2010.
 P. Antczak*, F. Soulet*, W.W. Kilarski*, J. Herbert, R. Bicknell, F. Falciani, A. Bikfalvi. Gene signatures in wound tissue as evidenced by molecular profiling in the chick embryo model. BMC Genomics 11(1): 495. 2010. (* Authors contributed equally)
 P.Antczak, F. Ortega, J.K. Chipman, F.Falciani. GMapping Drug Physico-Chemical Features to Pathway Activity Reveals Molecular Networks Linked to Toxicity Outcome. PloS one 5(8): 580-588. 2010.