Although every cell in an organism contains the same DNA, there is a great variety of cell types (e.g. skin, muscle, kidney) due to the fact that different genes are being transcribed. The amount of transcripts, or RNA, made from a specific gene can be measured in the cell and is referred to as the expression level of the gene. Understanding how, why, when and where genes are turned on and off is crucial for understanding many biological processes, ranging from devlopment to a variety of diseases, including cancer and autism.
Recent technological advances have made it possible to analyze gene expression and other related properties in a high-throughput manner, and this has resulted in a wealth of data. However, the experimental data is typically large, high-dimensional and noisy. We are interested in developing computational methods that will make it possible to extract as much information as possible from the data.