Dr. Orly Alter has been an Assistant Professor in the Department of Biomedical Engineering and a Fellow of the Institute for Cellular and Molecular Biology at the University of Texas at Austin since 2004. In 2005 she was selected to give the Linear Algebra and its Application Lecture of the International Linear Algebra Society. She was a National Human Genome Research Institute Individual Mentored Research Scientist Development Awardee in Genomic Research and Analysis from 2000 to 2005. From 1999 to 2003, she was a Sloan Foundation and Department of Energy Postdoctoral Fellow in Computational Molecular Biology in the Department of Genetics at Stanford University.

Dr. Alter received her Ph.D. in Applied Physics at Stanford University in 1999. In her thesis work she established the quantum theoretical limits to the information which can be obtained in the measurement of a single physical system about the system's quantum wavefunction, its time evolution and the classical potentials which shape this time evolution. For this work, she was an American Physical Society Outstanding Doctoral Thesis Research in Atomic, Molecular, or Optical Physics Award Finalist in 1998. This thesis work was published as a book, titled "Quantum Measurement of a Single System," by Wiley in 2001. Today Dr. Alter's thesis work is recognized as crucial to the field of gravitational wave detection.

The research in Dr. Alter's Genomic Signal Processing Lab is motivated by recent high throughput technologies, such as DNA microarrays, which make it possible to record the complete genomic signals that guide the progression of cellular processes. To this end, she built the first matrix computations models from these data, through adaptations and generalizations of mathematical frameworks that have proven successful in describing the physical world, in such diverse areas as mechanics and perception: the singular value decomposition (SVD) model, the generalized SVD (GSVD) comparative model and the pseudoinverse projection integrative model. She showed that her models provide mathematical descriptions of the genetic networks that generate and sense the measured data, where the mathematical variables and operations represent biological reality: The variables, patterns uncovered in the data, correlate with activities of cellular elements, such as regulators or transcription factors, that drive the measured signal, and cellular states where these elements are active. The operations, such as data reconstruction, rotation and classification in subspaces of selected patterns, simulate experimental observation of only the cellular programs that these patterns represent.

Dr. Alter illustrated these models in analyses of data from studies of the interconnected programs of cancer and the cell division cycle. Two alternative pictures of RNA expression oscillations during the cell cycle emerged, which parallel well-known designs of physical oscillators and convey the capacity of the models to elucidate the design principles of cellular systems as well as guide the design of synthetic ones. Recently, she also demonstrated the power of the models to predict previously unknown biological principles with a prediction of a novel mechanism of regulation that correlates DNA replication initiation with cell cycle-regulated RNA transcription in yeast. Dr. Alter's goal is to enable better understanding and ultimately also control of life processes on the molecular level. Her models may become the foundation of a future in which biological systems are modeled as physical systems are today. The novel mechanism of regulation she predicted may be at the basis of a future where the cell division cycle and cancer can be controlled.

Dr. Alter's research is cited in hundreds of scientific papers. Within a few months of their publication, these papers became part of the reading material in academic courses taught at schools of medicine as well as schools of natural sciences and engineering. Today, her work is featured in textbooks in linear algebra as well as computational molecular biology.