Scientific background
Medical, biological and biotechnological research is undergoing a revolution. Large-scale platforms for generating thousands of measurements in a single experiment have permeated all life science fields, and has led to the generation of terabytes of data relevant to the understanding of biological processes and systems.

This development has prompted an evolution of sophisticated computational analyzes of individual data types, but has also accentuated the need for know-how in integration of extremely diverse data types such as whole-genome sequences, genome-wide association studies, gene expression profiles, protein interaction networks, and unstructured text from patient records or scientific publications.

Data integration
Combining diverse data sets can give insight into diseases, mechanisms of action, side effects, or other systemic phenomena that would not otherwise emerge. Intomics consider this unprecedented situation as a window of opportunity rather than a problem within life science, where novel scientific and commercial achievements can be made using new, pioneering tools and technologies.

Selected, relevant publications
Nature 2006: Co-evolution of transcriptional and post-translational cell-cycle regulation
Nat. Biotech. 2007: A human phenome-interactome network of protein complexes implicated in genetic disorders
PNAS 2008: A large-scale analysis of tissue-specific pathology and gene expression of human disease