The algorithm, created by James Wang, holder of the PNC Career Development Professorship, and his collaborators, made it possible to dramatically accelerate the search for patterns among the staggering mass of information that makes up the human genetic code, as well as the genetic codes of other living creatures.  Called a Sequence Search Tree, or SST, the algorithm is believed to have quickened the pattern recognition pace twenty-fold.  The method does entail a slight loss in accuracy, but it significantly speeds up the mapping of genetic patterns.  The breakthrough was made possible by the way the SST algorithm indexes genetic information. 

Initially developed in 1999, SST has been used by an industrial partner of the National Human Genome Institute, a consortium of academic centers studying man’s genetic makeup.  The results of the institute’s project, as well as one being conducted by Celera Genomics, are expected to revolutionize the understanding and treatment of disease.  Scientists recently published early draft descriptions of the human genome.

The work on the algorithm was performed while Wang was a graduate student at Stanford University.  A paper “SST: An Algorithm for Searching Sequence Databases in Time Proportional to the Logarithm of the Database Size” was reported at the Annual Conference on Research in Computational Biology (RECOMB) and published in Currents in Computational Molecular Biology in 2000.  Wang and his team have applied for a patent for SST. 

2/20/01

For further information, contact Charles C. DuBois, (814) 865-4458 or news@ist.psu.edu

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