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Recent Patents in Bioinformatics, August — September, 2008

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US Patent 7,428,554. System and method for determining matching patterns within gene expression data. Inventors: Carter Coberley; James C. Diggans; Doug Dolginow; Michael Elashoff; Larry Mertz. Assignee: Ocimum Biosolutions.
 
Protects a computer-based system for retrieving information from “a number of data sources on a computer network containing biological data,” according to the patent abstract. The network database is organized in a b-tree configuration with several sample nodes. Each sample node includes a curated data set of pre-formatted and pre-computed summary biological data obtained from at least one biological sample. The sample nodes are organized in a hierarchical arrangement according to clinical relevance. A set of attributes is assigned to each sample node to aid navigation through the database using a browser. Search results include automated reports of the summary biological data stored in the sample nodes and custom reports generated using the summary biological data.
 

 
US Patent 7,428,527. Data distribution method, data search method, and data search system. Inventors: Tsunehiko Watanabe; Junji Yoshii; Tadashi Mizunuma; Yuichi Minesaki; Fumitoshi Ogura; Keisuke Yamamoto; Tateo Nagai. Assignee: Hitachi Software Engineering.
 
The patent abstract describes a method for extracting information from several databases in which information about biological substances, such as sequences of bases and proteins, is stored. Data is downloaded from the databases, and information is extracted from the downloaded data “indicating links between two databases, a detailed description of each data, and sequence data for homology search, which together constitute an index,” the abstract states. The extracted index is “distributed to a user facility, where a user conducts a search using the distributed index.”
 

 
US Patent 7,424,370. Computational method for identifying adhesin and adhesin-like proteins of therapeutic potential. Inventors: Gaurav Sachdeva; Kaushal Kumar; Preti Jain; Samir K. Brahmachari; Srinivasan Ramachandran. Assignee: Council of Scientific and Industrial Research (India)
 
Protects a computational method for identifying adhesin and adhesin-like proteins. The method computes the sequence-based attributes of a neural network software in which the attributes are amino acid frequencies, multiplet frequency, dipeptide frequencies, charge composition, and hydrophobic composition. The method trains the artificial neural network for each of the computed five attributes, and identifies the adhesin and adhesin-like proteins.
 

 
US Patent 7,424,369. Physical-chemical property based sequence motifs and methods regarding same. Inventors: Werner Braun; Venkatarajan S. Mathura; Catherine H. Schein. Assignee: Board of Regents, the University of Texas System.
 
Covers a data analysis system, such as a data-mining or data-exploration method, that uses physical-chemical property motifs. For example, the patent abstract states, “a sequence database may be searched for identifying segments thereof having physical-chemical properties similar to the physical-chemical property motifs.”
 

 
US Patent 7,416,524. System, method and computer program product for fast and efficient searching of large chemical libraries. Inventors: Victor S. Lobanov; Dimitris K. Agrafiotis; Francis R. Salemme. Assignee: Johnson & Johnson Pharmaceutical Research & Development.
 
Covers a computer program for “fast and efficient searching of large virtual combinatorial libraries based on a fitness function,” according to the patent abstract. The method first selects a set of reagent combinations at random from a virtual combinatorial library. “Each reagent combination in the first set is then enumerated to produce a first set of enumerated compounds,” according to the abstract. And certain of these enumerated compounds are selected based on the fitness function. The selected compounds are then deconvoluted into reagents to generate a focused library. A second set of enumerated compounds is then selected based on the fitness function, and these compounds “represent a near optimal selection of compounds based on the fitness function.”

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