Analysis of high throughput data and the unbiased interpretation of the data require novel ways of performing research. In this thesis we show novel methods for better quantification of multiplex array analysis of peptide phosphorylation. This quantification is necessary since, unlike the housekeeping gene expression used for the normalization and quantification of gene expression micro-arrays, housekeeping kinases that can be used for normalization and quantification are not present. In Chapter 2 therefore, we describe a novel method for normalization and quantification of data generated on a PepChip. Using this method we correct for signal gradients, artifacts, intensity distribution, intensity saturation and overshine from neighboring spots. Application of the resulting RSE (repetitive signal enhancement) protocol yielded better characterization of cellular physiology of drug treatment of cells from patients with myelodysplastic syndrome. Using this, we were able to better understand the signaling mechanisms dictating cell fate. An interesting observation when working with the PepChips was that the use of kinase substrates based on sequences derived from natural protein sequences, e.g. full-length proteins, protein fragments or short peptide sequences, often result in non-specific and insensitive kinase assays. Moreover, since there is a literature bias for the described kinase substrates, some kinases were underrepresented or overrepresented on the PepChip making kinome profiling based on natural kinase substrates quite impossible. We therefore show in Chapter 3 that it is possible to rationally design kinase peptide substrates that are both sensitive and selective for the desired kinase. We tested the sensitivity and selectivity of several designer peptides both in solution for measurement by mass spectrometry, as well as after immobilization of the peptides on a PepChip. The implication of this work is that we can now automatically design better kinome profiling PepChips by designing multiple selective and sensitive substrate peptides for a large part of the kinases in the kinome, resulting in unbiased kinome profiling for understanding cellular signal transduction networks. Intricate and complex signal transduction networks determine cell fate and malfunctioning networks underlie many diseases, including cancer, diabetes and osteoarthritis. Incomplete understanding of the network in References 1 Hunter, T. Protein kinases and phosphatases: the yin and yang of protein phosphorylation and signaling. Cell 80, 225-236, doi:0092-8674(95)90405-0 [pii] (1995). 2 Cohen, P. Targeting protein kinases for the development of antiinflammatory drugs.