The completion of the various genome projects has sparked the development of new powerful technologies and methods which allow the comprehensive and quantitative analysis of complex biological systems and which, in their turn, have revolutionized biological research.
Keeping pace with the fast developments in the field of post-genomic research we guide our research activities towards two main goals:
The deployment of post-genomic technologies for achieving ‘systems biology’ approaches to cancer.
We direct our efforts toward the use of post-genomic methodologies, mainly transcriptomics and genotyping, as a means to understand of the molecular mechanisms underlying oncogenesis, metastasis and responses to remedies.
DNA microarrays have proved to be one of the most powerful post-genomic technological platforms for unravelling new gene functions, for characterizing the genetic background, for perceiving molecular pathways and interactions and for exemplifying distinctive features of the complex biological systems. Nevertheless, over the years, it is becoming increasingly clear that we must combine information from different platform technologies to identify subgroups of patients and tumour subclasses so that we could arrive to more precise, predictive and individualized approaches to cancer treatment.
Within the “PrognoChip” project we aim to identify and validate “signature” gene expression profiles of tumours that correlate with epidemiological or clinical parameters. One of the main challenges of this prospective study is the development of interoperable and efficient clinico-genomic information systems for the integration and analysis of heterogeneous data.
The development of cancer biomedical informatics infrastructure for facilitating medical knowledge discovery and sharing of clinico-genomic data.
Integration of clinical, genetic and post-genomic information will allow researchers to elucidate molecular mechanisms underlying diseases and responses to therapy, identify pharmaceutical targets, and develop specific drugs. Nevertheless, post-genomic data are heterogeneous, require handling of vast genomic information and require powerful information infrastructures facilitating computational intensive processes.
In order to seamless integrate, handle, share and analyze the vast clinical and post-genomic information and the heterogeneous datasets, obtained by different technological platforms, we have initiated research activities towards the development and deployment of a cancer biomedical informatics grid environment providing advanced knowledge-discovery tools, interconnecting clinical research organisations and ensuring the appropriate privacy and security of clinical and genomic data.
In that context we are collaborating closely with the e-Health Laboratory of the Institute of Computer Science of FORTH.