Merging experimental data andin silicoanalysis: a systems-level approach to autoimmune disease and cancer

Abstract

Systems biology, or more specifically network biology, is driven by the assumption that a single gene is seldom accountable for a discrete biological function. In other words, studying molecules one by one will not satisfactorily address the function of complex organisms and/or predict the consequences of biological interactions. On the other hand, interpretation of large-scale data sets provided by the development of high-throughput techniques, which form the core of systems-level analysis, does raise methodological issues. Enhancement of such methodologies will be of key importance for health research in the coming years, as studies have provided convincing evidence that integration of experimental data with in silico analysis can lead to scientific advances that lay the foundations for translational research applied to human disease. These topics have been discussed in the present review and two case studies exemplifying our experience in the field have also been presented. We suggest that the process of integrating in silico analysis (dry laboratory) with experimental verification (wet laboratory) is likely to have a broad impact on the study of biological systems in physiology and disease.

Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps

“…Interpretation of genome-wide data obtained from cohorts of tumour samples using microarrays or massive sequencing technologies requires functional annotation tools. 60 , 61 For example, visualization of differentially expressed genes on top of biological pathway diagrams may provide insights into the molecular details of cancerogenesis. 39 ACSN can be used for visualization of both the individual gene expression levels and of the functional module activity level.…”

CDH11 inhibits proliferation and invasion in head and neck cancer

“…In silico analysis of existing datasets has become an important approach in identifying tumor‐specific networks and nominating molecular targets in head and neck squamous cell carcinoma (HNSCC) . Translational researchers use in silico analyses linked to clinical data to complement laboratory research.…”

Desmosome assembly, homeostasis, and desmosomal disease

“…This subnet included 28 accessory proteins, including kinases, phosphatases, and caspases. 61,62 Many of these molecules, such as PKC, Src, MAPK, epidermal growth factor receptor (EGFR), and caspase 2/3, are now known to be involved in the assembly and disassembly of desmosomes. 8,12,63,64 It is interesting to note that Pg, one of the main organizers of the desmosome that is crucial for adhesiveness, was highly connected to both protein kinases (n=5) and phosphatases (n=4), and this provided an in silico demonstration that the dynamic regulation of the desmosome may be orchestrated by this protein.…”