Project type: Basic Research and Application Project
Project duration: 2007 - 2009
Collaborators on project
With the advent of systems biology, research in genomic medicine and recent advances in biotechnology, biomedicine as a scientific discipline has become dependent on the computational tools to infer new knowledge from the experimental data. The research paradigms have shifted from single-gene research to genome-wide studies. One of the recent key approaches that replaced classical techniques are data-rich, large-scale phenotypes. Standard, morphological phenotypes that were most often observed in biomedical studies are no longer sufficient for system-based approaches. In the past few years, techniques in experimental biology have advanced to the point where the state of the organism can be represented with genome-wide measurements, and where such phenotypes can be measured in parallel across thousands of experimental conditions. The principal benefit of such phenotypes is in the amount of potential information they hold: instead of studying limited effects of medical treatments or observing the progress of diseases by some limited indicator, large-scale phenotypes could provide us with much richer, systemic information. As such phenotypes and technology to obtain them are only emerging, an obvious next step is to construct appropriate computational tools to address them. This is exactly the mission of the proposed project, within which we plan to develop a collection of computational approaches that use complex phenotypes in analysis of active components of chemical compounds, functional genomics (gene function prediction) and discovery of mechanisms of transcription regulation.
While primarily addressing the data from model organisms, the project’s principal target is to develop enabling technology for research in drug design, drug target identification and utility of large-scale phenotypes in diagnostic and prognostic procedures. The outcome of the project will consist of new computational methods, their software implementation in open-source data mining framework, and a set of utility studies in structure-activity analysis of drugs, functional genomics and inference of genetic pathways and gene sequence analysis.