Emerging paradigms in applied bioinformatics

biomarkers is an important goal for the pharmaceutical industry.Validation of innovative, highly specific and practical biomarkers would dramatically accelerate research on the etiology, pathophysiology, progression and prognosis of diseases. It would also facilitate the development of pharmacotherapies, including the identification of treatment responses, in terms of responders and non-responders, the understanding of side-effect profiles, and the individualization of therapies. Application of biomarkers per se, that is, biological markers of physiological events, pathophysiological processes, or responses to a therapeutic intervention, also includes defining surrogate biomarkers that can be substituted for a clinical endpoint and can be used to make risk–benefit assessments [1,2]. Several examples of surrogate biomarkers or endpoints have been established, such as the measures used to make decisions on cholesterol-lowering drugs [3], certain anti-retrovirals (e.g. CD4 count and HIV-1 RNA profiles in HIV) [4] and anti-hypertensive drugs.The first meeting on Biomarkers and Surrogate Endpoints: Advancing Clinical Research and Applications, organized by the National Institutes of Health and the US FDA in 1999, provided a comprehensive framework on the importance of the development and application of biomarkers and surrogate endpoints in clinical medicine and therapeutics. Another important area in the pharmaceutical industry is the identification and validation of new drug targets. In this area, gene expression technologies are key elements in target selection to study responses of biological systems for drug uptake and pharmacodynamics, or to study different pathophysiological conditions [5]. These technologies are crucial for identifying biomarkers of disease, predicting chemical toxicity and understanding why individuals show such a wide variability in their sensitivity to pharmacological agents or pathophysiological conditions [5].Thus, gene expression could play a crucial role within the modern pharmaceutical industry for therapeutic target gene selection and potential drug candidate selection. Different methods of RNA analysis can be used for gene expression profiling, such as northern blotting [6], RNase protection assay [7], reverse transcription polymerase chain reaction (RT-PCR) and in situ hybridization [8]. In the past decade, the TaqMan RT-PCR technique was developed and demonstrated to be a reliable and sensitive tool to quantify and monitor accumulating PCR products in real time [9–12].The method enables the direct detection of PCR products during the exponential phase of the reaction, combining amplification and detection in a single step. The use of TaqMan technology to monitor gene expression has become a standard research tool at both academic and industrial research institutions. Another important application of the TaqMan technology is validation …