Walter L. Ruzzo

Appointments and Affiliations

 
 
University of Washington
College of Engineering
Computer Science and Engineering
Professor, Appointed: 1977
Institute for Systems Biology
Visiting Professor, Appointed: 2002
University of Washington
School of Medicine
Genome Sciences
Adjunct Professor, Appointed: 2001
Professional Headshot of Walter Larry Ruzzo

Mailing Address

University of Washington
CSE, Box 352350
Seattle, Washington 98195
United States

Contact

Phone: (206) 543-6298
Fax: (206) 543-2969
ruzzo@cs.washington.edu
http://www.cs.washington.edu/homes/ruzzo/

Degrees

Ph.D., University of California, Berkeley, 1978.
B.S., California Institute of Technology, Mathematics, 1968.

Research Interests

Larry Ruzzo, Professor, received a B.S. (in Mathematics) from the California Institute of Technology in 1968, his Ph.D. (Computer Science) from the University of California at Berkeley in 1978, and has been with the University of Washington since 1977.

His research is focused on development of computational methods and tools applicable to practical problems in molecular biology, an increasingly data-rich discipline. Recent work has focused on methods for finding noncoding RNA (ncRNA) genes. A rush of discoveries in the last few years has greatly broadened appreciation of the biological diversity and importance of these genes, but analysis has been hampered by a lack of sensitive, specific and/or fast computational tools. His group has developed new techniques for inference of and sequence searching with covariance models, a leading approach for modeling ncRNA gene families. The inferred models show high sensitivity and specificity and the search tools typically accelerate searches by 100 fold or more with (provably) no loss in accuracy. These tools have been instrumental in the discovery of many new families of riboswitches. Application to genome-scale analysis and discovery of other new ncRNA families are both underway. His group also has expertise in analysis of gene expression array data including classification and clustering, sequence analysis problems such as computational gene prediction, and analysis of chromatin immunoprecipitation and high throughput sequencing data. Students have been deeply involved in and critical to the success of all stages of all of these research projects.

Recent Publications

2014
2013
2012
Bolouri, H, Ruzzo WL.  2012.  Integration of 198 ChIP-seq Datasets Reveals Human cis-Regulatory Regions.. Journal of computational biology : a journal of computational molecular cell biology. 19(9):989-97. Abstract
2010
2008