The biological sciences have become more quantitative and information-driven
since emerging computational and mathematical tools facilitate collection and
analysis of vast amounts of biological data. Complexity analysis of biological
systems provides biological knowledge for the organization, management, and
mining of biological data by using advanced computational tools. The biological
data are inherently complex, nonuniform, and collected at multiple temporal and
spatial scales. The investigations of complex biological systems and processes
require an extensive collaboration among biologists, mathematicians, computer
scientists, and engineers to improve our understanding of complex biological
process from gene to system. Lectures in the summer school expose attendees to
the latest developments in these emerging computational technologies and facilitate
rapid diffusion of these mathematical and computational tools in the biological
sciences. These computational tools have become powerful tools for the study of
complex biological systems and signals and can be used for characterizing variability
and uncertainty of biological signals across scales of space and time since the
biological signals are direct indicators of the biological state of the corresponding
cells or organs in the body.