US Patent 7,373,256. Method for the identification of molecules and biomarkers using chemical, biochemical and biological data. Inventors: Jeremy K. Nicholson, Elaine Holmes, Olivier Cloarec, Derek J. Crockford, John C. Lindon, Mattias Rantalainen. Assignee: None.
Protects an approach that uses multivariate statistics to analyze chemical, biochemical, and biological data, including spectral data such as nuclear magnetic resonance data. These methods are useful in metabonomics, proteomics, transcriptomics, and genomics according to the patent abstract, “and form a part of other methods, for example, methods for the identification of chemical species, methods for the identification of biomarkers that are useful in methods of classification, diagnosis, prognosis, etc.”
US Patent 7,370,021. Medical applications of adaptive learning systems using gene expression data. Inventors: Anthony Edmund Reeve, Mathias Erwin Futschik, Michael James Sullivan, Nikola Kirilov Kasabov, Parry John Guilford. Assignee: Pacific Edge Biotechnology.
Protects a neural network module that includes an input layer with one or more input nodes that are configured to receive gene expression data. The module also has a rule-based layer “comprising one or more rule nodes and an output layer comprising one or more output nodes configured to output one or more conditions,” according to the patent abstract. The module also includes an adaptive component that is configured to extract one or more rules from the rule-based layer and to represent relationships between the gene expression data and the conditions.
US Patent 7,365,311. Alignment of mass spectrometry data. Inventor: Lucio Cetto. Assignee: The MathWorks.
Covers methods, systems, and media for aligning mass spectrometry data before the data is analyzed. The mass spectrometry is re-sampled using a smooth warping function, according to the patent abstract. To estimate the warping function, the method uses a synthetic signal that is built using, for example, Gaussian pulses centered at a set of reference peaks, which may be designated by users or calculated after observing a group of spectrograms. “The synthetic signal is shifted and scaled so that the cross-correlation between the mass spectrometry data and the synthetic signal reaches its maximum value,” the patent abstract states.
US Patent 7,363,168. Adaptive baseline algorithm for quantitative PCR. Inventors: Roger Taylor, Alan Ridgeway Orr. Assignee: Stratagene (now Agilent).
Protects baseline subtraction algorithms to reduce tube-to-tube and cycle-to-cycle variability during real-time PCR amplification. The algorithms determine the threshold cycle for the first reliable detection of the amplified nucleic acid product.
US Patent 7,363,166. Computational method for the identification of candidate proteins useful as anti-infectives. Inventors: Samir Kumar Brahmachari, Srinivasan Ramachandran, Tannistha Nandi, Chandrika Bhimarao. Assignee: Council of Scientific & Industrial Research (India).
Protects a method for identifying candidate proteins in pathogens that could be useful as anti-infectives. Specifically, the patent describes “a novel computational method involving calculation of several sequence attributes and their subsequent analysis [will] lead to the identification of some outlier proteins in different pathogens which are either vaccine candidates, diagnostics, or drug targets,” according to the patent abstract.
US Patent 7,363,165. Significance analysis of microarrays. Inventors: Virginia Goss Tusher, Robert Tibshirani, Gilbert Chu. Assignee: The Board of Trustees of the Leland Stanford Junior University.
Protects a method, Significance Analysis of Microarrays, that assigns a score to each gene based on the change in gene expression relative to the standard deviation of repeated measurements. “For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of such genes identified by chance, [and] the false discovery rate,” according to the patent abstract.
US Patent 7,359,537. DNA microarray image analysis system. Inventor: Atsushi Mori. Assignee: Hitachi Software Engineering.
Covers a pattern-recognition system for handling an image of a DNA microarray, “and particularly relates to an image analysis system for a Stanford-type microarray having a plurality of blocked spots,” according to the patent abstract. The patent claims a microarray image analysis system in which “the user determines a status of a spot, the pixel value matrix of an image in a spot region is learned by a neural network, a vertically and horizontally symmetrical image, and an image rotated about the center of the region are formed and are learned by the neural network, and the neural network formed by repeating these steps is used for automatically recognizing the status of an undecided spot.”
US Patent 7,356,416. Method and system for automated inference creation of physico-chemical interaction knowledge from databases of co-occurrence data. Inventor: William B. Busa. Assignee: Cellomics.
Protects a system that automatically infers physico-chemical interaction knowledge from databases of term co-occurrence data. The co-occurrence data includes co-occurrences between chemical or biological molecules or co-occurrences between chemical or biological molecules and biological processes, according to the patent abstract. “The method and system may also help facilitate the abstraction of knowledge from information for biological experimental data and provide new bioinformatic techniques,” the patent abstract states.
US Patent 7,353,152. Method and apparatus for computer modeling diabetes. Inventors: Paul Brazhnik, Kevin Hall. Dave Polidori, Scott Siler, Jeff Trimmer. Assignee: Entelos.
Protects a mathematical and computer model of diabetes-related disorders. The model includes a representation of physiological control mechanisms directing, for example, fat metabolism, protein metabolism and/or carbohydrate metabolism. In one embodiment, “the model can account for the interconversion between macronutrients, as well as their digestion, absorption, storage, mobilization, and adaptive utilization, as well as the endocrine control of these processes,” according to the patent abstract. “In this embodiment, the model can simulate, for example, a heterogeneous group of diabetes-related disorders, from insulin resistant to severe diabetic, and can predict the likely effects of therapeutic interventions.”
US Patent 7,349,811. Gene mining system and method. Inventors: Lee A. Bulla Jr., Mehmet Candas. Assignee: Board of Regents, the University of Texas System.
Covers a system for targeting and cloning gene sequences based on functional observations from data mined from available gene databases. The patent claims a method in which one or more phenotypic characteristics are selected, and then a gene sequence is selected that is known to have the selected phenotypic characteristics. In addition, one or more databases containing cataloged gene sequences are also selected. “The selected gene sequence is compared to the cataloged gene sequences, and any cataloged gene sequences that contain a portion of the selected gene sequence are extracted,” according to the patent. The extracted gene sequences are prioritized based on the alignment of the selected gene sequence. “At least one of the prioritized gene sequences is selected based on one or more phenotypic criteria. Finally, one or more degenerate primers are designed to target the selected-prioritized gene sequences.”
US Patent 7,348,143. Method of visualizing non-targeted metabolomic data generated from Fourier transform ion cyclotron resonance mass spectrometers. Inventors: Douglas Heath, Dayan Goodenowe. Assignee: Phenomenome Discoveries.
Protects a method of displaying spectroscopic data as well as data structures comprising spectroscopic data.