Health Discovery Corporation has announced that it has received a Notice of Allowance from the U.S. Patent and Trademark Office for its patent application entitled “Method for the Manipulation, Storage, Modeling, Visualization and Quantification of Datasets.”
Once issued, the patent will be the second of a series of applications covering the Fractal Genomics Modeling (FGM) Technology to issue. This patent covers use of the FGM technology for identifying patterns within a dataset by recognizing repeated data strings within a long sequence of data, then associating each repeated string with a single point within a grid.
The points are then used to create a visual map which is capable of graphically representing the complete dataset. The claims of the new patent are not limited to biotechnology applications, but also encompass application of the FGM technology to pattern recognition within other types of data.
The FGM technology has been used to recognize patterns within gene expression data and causal relationships between genes to identify biomarkers that may be useful in developing potential treatments, diagnoses or prognoses of diseases, including HIV and leukemia.
In addition to its applications in biomarker discovery, FGM technology has clear applications in data compression for image data and other data types that involve datasets made up of repeated data strings of varying lengths.
Health Discovery Corporation also reported that the European Patent Office has recently granted a new patent covering the FGM technology. The claims of European Patent No. 1252588 correspond to those of the first issued U.S. patent covering the FGM technology, Patent No. 6,920,451, which provides for either graphical or mathematical mapping of the points that represent strings of data.
Once the USPTO issues the new FGM patent, Health Discovery Corporation will hold the exclusive rights to 26 issued U.S. and foreign patents covering uses of SVM and FGM technology for discovery of knowledge from large data sets.
Other issued patents cover methods and systems for pre-processing of data to enhance knowledge discovery using SVMs, analysis of data using multiple support vector machines and for multiple data sets, and providing SVM analysis services over the Internet.