| GOVERNMENT OF THE UNITED STATES, REPRESENTED BY THE SECRETARY, DEPARTMENT OF HEALTH AND HUMAN Patent applications |
| Patent application number | Title | Published |
|---|
| 20120129151 | Quantitative Real-Time Assay For Noroviruses And Enteroviruses With Built In Quality Control Standard - A method is provided for reverse transcription-polymerase chain reaction (RT-PCR) accomplished by: a) amplifying a reverse transcribed cDNA in a mixture containing Norovirus Genogroup I and Norovirus Genogroup II primers and probes, in which the Norovirus primers and probes can distinguish between Genogroup I and Genogroup II viruses; b) quantifying virus; and c) normalizing data based on a universal internal RNA control. Optionally, the method may also include primers and probes for Enteroviruses. The present invention also provides a reaction mixture comprising containing Norovirus Genogroup I and Norovirus Genogroup II primers and probes, in which the Norovirus primers and probes can distinguish between Genogroup I and Genogroup II viruses and universal internal RNA control primers and probes. | 05-24-2012 |
| 20120046878 | METHODS FOR ANALYZING HIGH DIMENSIONAL DATA FOR CLASSIFYING, DIAGNOSING, PROGNOSTICATING, AND/OR PREDICTING DISEASES AND OTHER BIOLOGICAL STATES - A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition. | 02-23-2012 |
| 20090035766 | Methods for Analyzing High Dimension Data for Classifying, Diagnosing, Prognosticating, and/or Predicting Diseases and Other Biological States - A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition. | 02-05-2009 |
