Orly Alter

Alter, Orly
Assistant Professor, Department of Biomedical Engineering
Fellow, Institute for Cellular and Molecular Biology

E-mail: orlyal@mail.utexas.edu

Website: http://www.bme.utexas.edu/research/orly/

Main Office: MBB 3.232
Phone: (512) 471-7939

Mailing Address:
Department of Biomedical Engineering
Institute for Cellular and Molecular Biology and Institute for Computational Engineering and Sciences
University of Texas at Austin
Austin, TX 78712-0159
Research Summary:
   In her Genomic Signal Processing Lab at UT Austin, Dr. Orly Alter and her students use generalizations of mathematical frameworks that have proven successful in describing the physical world to model large-scale molecular biological data, such as DNA microarray data. DNA microarrays make it possible to record the complete genomic signals that guide the progression of cellular processes. Future discovery and control in biology and medicine will come from the mathematical modeling of these data. To this end, Dr. Alter built the first predictive models of DNA microarray data using matrix computations. She demonstrated the ability of her 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 mRNA expression. This research work is cited in hundreds of scientific papers and several textbooks. It has become a part of the academic core curriculum in courses in mathematics and molecular biology.

   In 2007 Dr. Alter has been awarded more than $1.5 million in an R01 Grant from the National Human Genome Research Institute (NHGRI). This grant will support a five-year project in her lab, titled "Tensor Computations For Modeling Large-Scale Molecular Biological Data: From Discovery of Patterns to Discovery of Principles of Nature."

   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 predicted mechanism of regulation may be at the basis of a future where the cell cycle and cancer can be controlled.
 
Research Images:

Eigenvalue Decomposition (EVD) of a Genomic Network

EVD Subnetworks of a Genomic Network

 
Publications:
Global Effects of DNA Replication and DNA Replication Origin Activity on Eukaryotic Gene Expression (2009) Nat Mol Sys Biol 5, 312.
A Tensor Higher-Order Singular Value Decomposition For Integrative Analysis of DNA Microarray Data From Different Studies (2007) Proc Nati Acad Sci USA 104, 18371–18376 (supplemental material at http://www.bme.utexas.edu/research/orly/HOSVD/).
Discovery of Principles of Nature from Mathematical Modeling of DNA Microarray Data (2006) Proc Nati Acad Sci USA 103, 16063–16064 (reprint at http://www.bme.utexas.edu/research/orly/publications/PNAS_Commentary_2006.pdf).
Singular Value Decomposition of Genome-Scale mRNA Lengths Distribution Reveals Asymmetry in RNA Gel Electrophoresis Band Broadening (2006) Proc Nati Acad Sci USA 103, 11828–11833 (supplemental material at http://www.bme.utexas.edu/research/orly/harmonic_oscillator/).
Reconstructing the Pathways of a Cellular System from Genome-Scale Signals by Using Matrix and Tensor Computations (2005) Proc Nati Acad Sci USA 102, 17559–17564 (supplemental material at http://www.bme.utexas.edu/research/orly/network_decomposition/).
Integrative Analysis of Genome-Scale Data Using Pseudoinverse Projection Predicts Novel Correlation Between DNA Replication and RNA Transcription (2004) Proc Nati Acad Sci USA 101, 16577–16582 (supplemental material at http://www.bme.utexas.edu/research/orly/pseudoinverse/).

 
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