Signal Reconstruction and Analysis of Nonuniformly Sampled Temporal Microarray Data

Project: Research

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Many microarray (DNA chip) experiments are designed to make measurements at different time points, and the data for each gene can be considered as a digital signal. Analysis of these data is very difficult because they can be nonuniformly sampled in the temporal direction, the number of time points in each signal is very small, and the data can be distorted by noise. This project will study signal processing and analysis problems systematically for nonuniformly sampled temporal microarray data. The researchers will investigate the signal sampling and reconstruction problems in the so-called shift-invariant spaces, which overcome several limitations of the traditional signal sampling theories and reconstruction methods. They will introduce constraint sets, which represent prior knowledge about signals from different genes and their relations, to recover useful information in the signals and regularize the reconstruction process. They will also develop spectral analysis, feature extraction, and data classification techniques using the reconstruction result. The work will make significant theoretical contributions to the emerging microarray technology in addition to the field of signal sampling and reconstruction and the research results will find many useful applications, such as being built into data analysis tools for industry and biomedical researchers.


Project number9041268
Grant typeGRF
Effective start/end date1/01/0816/02/12