Statistical Signal Processing in the Post-Genomic Era

Organizers: Hagit Messer-Yaron (Tel Aviv University) and Amir A. Handzel (BG Medicine, Inc.)

Until a few years ago, much of the research in molecular biology focused on questions regarding specific genes. Explosive advances in technology have precipitated a deluge of experimental and theoretical work, highlighted by the complete sequencing of the human genome. Scientists now have access, not only to large amounts of data, but to data of novel types which give rise to new scientific questions. Broad molecular profiling of proteins and metabolites has opened a new window onto cellular processes, while the richness and the amount of the accumulated data, coupled with global analysis tools, have led to new studies in functional genomics and the first steps in charting intricate gene regulatory networks.

This expanding field and its new directions of research require innovative approaches and cross-disciplinary fertilization. The signal processing community, with its large body of knowledge and techniques, is especially well equipped to contribute to this endeavour, and in return, it can benefit from tackling new types of problems which necessitate the development of new methods. The special session will serve as a platform to survey the state-of-the-art in the field and the current use of signal processing in molecular biology with lectures by prominent researchers who have been breaking ground in various directions. We aim to stimulate interest of signal processing practitioners to these fascinating challenges.

Overview lecture:
  Author: Amir Handzel (BG Medicine, Inc.)
  Title: Signal processing challenges in the post-genomic era

Regular lectures:

• Title: On the use of Sequential Monte Carlo to Approximate the Optimal Filter Sensitivity for Parameter Estimation
  Authors: Hagit Messer (Tel Aviv University) and Ram Sever
• Title: Piloting and resampling in sequential Monte Carlo
  Author: Jun Liu (Harvard University)
• Title: Statistically significant gene regulation network discovery
  Authors: Al Hero (University of Michigan Ann Arbor) with Dongxiao Zhu
• Title: Gene clustering in gene regulatory networks identification
  Author: Ahmed Tewfik (University of Minnesota)
• Title: Engineering digital, analog, and transient behavior in individual cells and cell communities
  Author: Ron Weiss (Princeton University)