SSPM 2015 - Symposium on Signal Processing and Mathematical Modeling of Biological Processes with Applications to Cyber-Physical Systems for Precise Medicine

Recent progress in genomics, proteomics, metabolic phenotyping and physiological sensing revealed that numerous biomarkers representing collections of malfunctioning molecular regulatory pathways can serve for early detection of abnormal pathophysiology. This opens the possibility of designing complex cyber-physical systems for precise medicine capable of monitoring bio-molecular markers and physiological processes, mining their multiscale web of interactions, detect abnormal trends, and compute control-based therapeutic strategies.
One fundamental step in this new paradigm is represented by the mathematical methods used for processing sensed biological processes. Many of these biological processes exhibit complex multi-scale and nonlinear dynamics with pronounced non-stationary behavior raising numerous challenges for signal processing techniques. From a medical perspective, it becomes clearer that for an accurate assessment of deviations from homeostasis there is an urgent need for a multi-dimensional (i.e., considering numerous genomic, proteomic and metabolic biomarkers as well as physiological signals), multi-organ (i.e., accounting for influences on the biological dynamics between multiple organs) and multi-scale (i.e., scrutinize spatio-temporal correlations) analysis. On the same time, combining the richness of multi-modal sensing capabilities (e.g., audio, electrical, mechanical, chemical / metabolic) can not only enable more accurate mathematical modeling and better control strategies, but also a more rigorous understanding of biological dynamics in both healthy and disease states. In turn, the signal processing methods and their accuracy also affect the subsequent steps such as the mathematical modeling, parameter estimation, mining and control of biological processes. In addition, signal processing and mathematical modeling can contribute not only at deciphering diseases precursors, finding new therapeutic strategies, but also at understanding fundamental scientific challenges related to biological evolution and disease complexome.
This symposium addresses timely and the challenging aspects of signal processing for enabling the design of cyber-physical systems for precise and personalized medicine. Over the last decade, these interdisciplinary research communities have matured and their convergence can enable breakthrough solutions. The symposium will cover signal processing and mathematical modeling techniques aimed at advancing our understanding of the complex inter-dependencies between genomic, proteomic, metabolic and physiological processes. A special emphasis will be put on highlighting the main challenges we face in these disciplines. This symposium will provide a platform for discussion and dissemination of research on topics of interest, but not limited to the following:
???? Genomic signal processing
???? Functional genomics
???? Algorithmic and mathematical techniques for genome analysis
???? Computational proteomics
???? Structural bioinformatics
???? Mathematical modeling for metabolomics and physiological processes
???? Phylogenetics (phylogeny estimation, models of evolution, comparative biological methods, population genetics)
???? Genetics and population analysis (linkage analysis, association analysis, population simulation, marker discovery, genotype calling)
???? Mathematical techniques for analyzing high-throughput biological data
???? Machine learning algorithms and techniques in bioinformatics
???? Mathematical methodologies for system biology (multiscale modeling, network of networks)
???? Mathematical modeling of cell physiology, tissues, organs and systems