A vast amount of information can be contained in image data about the phenotype of cells, and potentially about the molecular-scale causes of phenotype. A challenge is how best to quickly and accurately quantitate these intracellular responses. Quantitative microscopy and image processing allows automated data collection and analysis on a cell-by-cell basis. The challenge to be undertaken is to quantitatively assess a large number of biomarkers simultaneously. Achieving this may require the use of novel probes, engineering of indicator cell lines, combining modes of collecting image data, and the development of image analysis algorithms. At least some of these data can be collected on live cells in real time and thus provide kinetic information about an intracellular process. To understand cause and effect between parameters will require collation of data into a data base and development of Bayesian logic to describe the signaling process. A goal is to develop a matrix of biomarkers that contribute to a signaling pathway and to identify their temporal or spatial relationships. A model system based on cytotoxicity pathways could be used.
Cell signaling; Fluorescence microscopy; Green fluorescent protein; Image processing; Transfection;