Biomedical Informatics: Mathematical Techniques, Computational Challenges & Imaging-Genetics Applications
Abstract: Contemporary informatics employs multidisciplinary techniques to address challenging biomedical problems using heterogeneous data, e.g., imaging, phenotypic and genotypic data. The informatics community needs novel mathematical approaches, robust computational algorithms and efficient hardware infrastructure that enable modeling, analysis and visualization of data and results in large-scale studies. There is a significant push for developing, validating, integrating and distributing diverse computational resources and web-services for processing, analyzing and visualizing large amounts of biomedical data. This talk will discuss specific biomedical informatics challenges, mathematical modeling and statistical techniques, computational infrastructure, and research findings. Examples will include classification of spatially unaligned fMRI data, clustering in medical imaging and clinical data, computational brain atlasing, biological shape representations, Bayesian network modeling, and statistical analyses of biological manifolds. We will also discuss interoperability of disparate computational resources and graphical design, management and execution of complex informatics and genomics workflows.
Dynamics of neural activity at different integrative scales.