the Response of Biological Materials to Toxic Agents

The detection of biological and chemical toxins has become one of the main con-cerns in environmental and military fields. In this framework, the department of Micro-biology and Biochemistry at Oregon State University has discovered that fish living cells are promising indicators of the presence of a wide range of toxins. Thus, an interdis-ciplinary project called ”SOS Cytosensor ” was launched to create an autonomous and mobile device to detect such toxins using these living cells. After exposing a cell culture to a specific biological or chemical agent, a sequence of cell images is recorded. The extraction of features from the experimental sequences of images results in time series that have to be modelled and classified in order to prove useful in toxin detection. The chosen models should give a representation of time series that supports accurate classification and clustering and that would also make storage and transmission more efficient. There are many techniques for dimensionality reduction of time series data in the literature, such as Fourier transforms, but segmentation is the most popular technique for extracting structures from time series. Segmentation algorithms can be classified as batch or online. The main idea is that given a tim