Mathematical Biology Seminar

Orly Alter
Bioengineering and Scientific Computing and Imaging (SCI), University of Utah
3:05PM, Wednesday, October 6, 2010
LCB 225
Discovery of Cellular Mechanisms and Prognosis of Cancers from Mathematical Modeling of DNA Microarray Data


Future discovery and control in biology and medicine will come from the mathematical modeling of large-scale molecular biological data, such as DNA microarray data, just as Kepler discovered the laws of planetary motion by using mathematics to describe trends in astronomical data [1].

In this talk, I will first describe novel generalizations of the matrix and tensor computations that underlie theoretical physics (e.g., [2,3]). In my Genomic Signal Processing Lab we are developing these computations for comparison and integration of multiple high-dimensional datasets recording different aspects of, e.g., the cell division cycle and cancer.

Second, I will describe the prediction of a previously unknown mechanism of regulation by using these computations to uncover a genome-wide pattern of correlation between DNA replication initiation and mRNA expression during the cell cycle [4,5]. This computational prediction was recently experimentally verified by analyzing global mRNA expression levels in synchronized cultures under conditions that prevent DNA replication initiation without delaying cell cycle progression [6].

Last, I will describe the computational prognosis of brain cancers by using these computations to compare global DNA copy numbers in patient-matched normal and tumor samples from the Cancer Genome Atlas [7].


1. Alter, PNAS 103, 16063 (2006);

2. Alter, Brown & Botstein, PNAS 100, 3351 (2003);

3. Ponnapalli, Saunders and Alter, under review.

4. Alter & Golub, PNAS 101, 16577 (2004);

5. Omberg, Golub & Alter, PNAS 104, 18371 (2007);

6. Omberg, Meyerson, Kobayashi, Drury, Diffley & Alter, MSB 5, 312 (2009);

7. Lee & Alter, 60th Annual Meeting of the American Society of Human Genetics (ASHG), Washington, DC, November 2-6, 2010.