Numerical models and methods for cell image analysis

常见疾病，如中风，糖尿病，哮喘和癌症，每年在加拿大造成大量的医疗保健支出。这些疾病通常是由环境因素与遗传易感个体相互作用引起的。了解调控基因网络如何影响细胞功能将有助于治疗常见疾病。然而，将基因、疾病和治疗联系起来是非常耗时的。这涉及从天然和遗传干扰的细胞收集大量数据。近年来，DNA微阵列技术的发展使细胞生物学家能够通过高通量实时成像系统快速记录细胞活动。由于每次实验都会产生数千张图像，传统的手动或交互式计算机辅助跟踪将不再可行。用于跟踪细胞行为的有效和可靠的软件在分析细胞图像中变得至关重要。

Common diseases such as stroke, diabetes, asthma, and cancer result in substantial health care expenditure in Canada every year. These diseases are often caused by environmental factors interacting with genetically susceptible individuals. Understanding how the regulatory gene networks affect cell function will facilitate treatment of common disorders. However, linking genes, diseases, and treatments is time-consuming. This involves collection of massive amounts of data from native and genetically perturbed cells. The recent DNA microarray technology allows cell biologists to quickly record cell activities by high-throughput real-time imaging systems. With thousands of images generated in each experiment, the traditional manual or interactive computer-assisted tracking would no longer be feasible. Efficient and reliable software for tracking cellular behaviour becomes critical in analyzing the cell images.