Integrated biomedical data analysis utilizing various types of data for biomarkers identification

Biomarkers discovery research requires the integrated analyses of a variety of the data across multiple domains, including clinical data, pathology data, gene expression, epigenetic data. Proper analysis can help understand the biological mechanism and better interpret the impact of the markers to disease. Realising the nature of the data in biomedical research and translational biomedicine, we developed a data analysis pipeline with a set of computational functions and an integrated method that can serve as a template for many biomarkers discovery research. The data analysis pipeline was developed with the data collected to identify biomarkers associated with obesity related disease. The set of functions included in the analysis template were used for finding the biomarkers and their combinatorial effect associated with obesity. The functions were developed in the general way that can be extended to other study easily.