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Methods and Implementations for Storing Sparse Vectors

Technology Benefits: Lossless compression

Technology Application: Database searching, drug discovery, cheminformatics

Detailed Technology Description: None

Others

Additional Technologies by these Inventors

Integrative Approach for the Analysis and Visualization of Static or Dynamic Omic Data, Including Genomic, Proteomic, Gene Expression, and Metabolic Data

Tech ID/UC Case

21322/2007-793-0

Related Cases

2007-793-0

*Abstract: This invention consists of a set of methods and algorithms to compress the information contained in large vectors of binary or integer variables. These vectors occur in a variety of applications where objects are represented by spectral fingerprints, which by nature tend to be large and sparse. By leveraging the power law distributions often observed in these spaces, researchers at UCI have developed new lossless compression methods using integer entropy coding. In contrast to current compression systems requiring 1024 bits to store each molecule, the UCI methods can achieve lossless compression to a mere 300-400 bits.

*Principal Investigator: Name: Pierre Baldi
Department:

Name: Daniel Hirschberg
Department:

Name: S. Joshua Swamidass
Department:

Country/Region: USA

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