Fuzzy Fractal Analysis of Molecular Imaging Data

Recent advances in biomedicine, pharmacology, and biotechnology open doors to the understanding how diseases are developed at the molecular and physiological level. This gain of understanding tremendously helps facilitate the design and discovery of drugs for therapeutic treatment. Despite the advances in the technology and new knowledge in systems biology, drug discovery is still a low process without utilizing scientific computations that allow precise and rapid analysis of biological processes under trials. This paper particularly addresses fractals as a computational tool for analyzing molecular imaging data that appear to be very useful sources of information for understanding the interactions and behaviors of complex biological networks and the development of predictive medicine. We study herein some fractal characteristics of fluorescent microscope images of peroxisomes, and propose the conceptual frameworks of fuzzy mixture fractal dimensions and fractal distortion measures for bioimage classification.