US Patent 6,816,790. Method and apparatus for determining gene expression levels. Inventors: Geoffrey Grinstein, Glenn Allen Held, Yuhai Tu. Assignee: International Business Machines.
Covers techniques for analyzing gene expression levels. In one aspect, the invention provides a method for determining a concentration level of a target nucleic acid that determines a measure of affinity value of the target oligonucleotide with a probe oligonucleotide, along with a hybridization intensity value for the target oligonucleotide and the probe oligonucleotide at a probe spot. The measure of affinity value and the hybridization intensity value are used to determine the concentration level of the target nucleic acid.
US Patent 6,816,789. Method and system for analyzing chromatograms. Inventor: Jean-Louis Excoffier. Assignee: Varian.
Protects a system for chromatogram analysis based on a method for reducing each chromatogram to a data set that can be compared to another data set, producing a comparison result that indicates the similarity or dissimilarity of the two chromatograms. The invention provides a system and method that can be used to identify DNA sequence variations through chromatogram analysis as well as a user interface to display results of chromatogram analysis and illustrate which samples are dissimilar or similar to reference chromatograms.
US Patent 6,813,615. Method and system for interpreting and validating experimental data with automated reasoning. Inventors: Ricardo Colasanti, Mark Collins, John Shaw. Assignee: Cellomics.
Protects a system for interpreting experimental data in which domain-specific knowledge is acquired from one or more pharmaceutical information sources; a semantic representation of the domain-specific knowledge is created meeting a desired set of criteria; and then pharmaceutical data from a knowledge database is classified with the semantic representation, allowing construction of a set of reasons for any classified pharmaceutical data. According to the inventors, the set of reasons may help interpret the classified pharmaceutical data to remove errors, and may improve identification, selection, validation, and screening of new real or virtual pharmaceutical compounds.