If you want to submit to the special session, please select these topics on the paper submission form
Machine Learning for Genomic Signal Processing
organized by Prof. Man-Wai Mak
With the recent advances in DNA microarray technologies, it has become possible to measure the expression level of thousands of genes simultaneously. The ability to discover hidden patterns in gene expression data has significant impact on drug design and the development of new treatments with maximum efficacy and minimum side effects. However, the large number of genes together with the complexity of gene expression patterns make interpreting the million of biological measurements a challenging task. Machine learning will play an important role in meeting this challenge. This special session aims to explore various machine learning techniques for the processing and analysis of gene expression data.
Biomedical Imaging and Data Fusion
Organized by Vince Calhoun & Tulay Adali
With multiple imaging modalities available to biomedical imagers today, each with specific advantages and disadvantages, there is a need for methods that are able to take advantage of the information available. This special session will provide some examples of techniques for processing high dimensional biomedical imaging data and for doing data fusion of multi-modal imaging (e.g. EEG and fMRI).