Prevention and personalized medicine are key issues of contemporary medical research. Multi-OMICS approaches aim at measuring the dynamics of the most important biomolecules (i.e. genes, mRNAs, proteins and metabolites) in order to gain better understanding of the complex regulation of a cell. In the medical context, such efforts are promising for the discovery of novel biomarkers and the development of new drug targets. However, processing and interpretation of multi-OMICS data is usually challenging and requires a structured workflow (Fig. 1).
Within the multi-OMICS pro-ject named PROFILE data sets obtained from several high - throughput technology platforms (Transcriptomics, Proteomics, Epigenetics, cirulating tumor cells) are analysed. For this data processing a standardized workflow has been developed (Fig.1), which comprises several steps of data conversion, quality control, data comparison, text mining and statistical analyses. Additionally, a software named CrossPlatformCommander (XPlatCom) has been programmed, which facilitates several steps of the proposed workflow in a semi-automatic manner. XPlatCom is currently in development (Beta status).
A more detailed description of the software is given by the poster available for download below and by the literature (PMID:23501674).
Figure 1: Sketch of the data processing workflow within the PROFILE project. Note, that transparent parts of the sketch indicate data processing steps, which will be implemented within XPlatCom in the near future.
Michael Kohl (michael.kohl:at:rub.de)