Representation and extraction of biclusters from data arrays
First Claim
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1. A method of data mining for biclusters in data at least partially using a processor in communication with a memory storing instructions for execution by the processor to perform the method, the method comprising detecting hyperplanes in said data, said hyperplanes having at least two dimensions and obeying an equation
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Abstract
Gene expression, or other data is analyzed for the presence of biclusters. The data is represented as geometric data. Lines, planes and/or hyperplanes are detected in the geometric data using a transform such as a Hough Transform or its variations. The detected lines, planes and hyperplanes are analyzed to determine if they correspond to biclusters in the original data.
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Citations
24 Claims
- 1. A method of data mining for biclusters in data at least partially using a processor in communication with a memory storing instructions for execution by the processor to perform the method, the method comprising detecting hyperplanes in said data, said hyperplanes having at least two dimensions and obeying an equation
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14. A method of analyzing data for biclusters, at least partially using a processor in communication with a memory storing instructions for execution by the processor to perform the method, the method comprising:
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transforming said data into parameter space by applying a transform to the data; detecting hyperplanes having at least two dimensions and obeying an equation - View Dependent Claims (15)
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16. Apparatus for analyzing data for biclusters comprising a processor in communication with a memory storing instructions for execution by the processor to perform a method, the method comprising:
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transforming said data into parameter space by applying a transform to the data; detecting hyperplanes in said transformed data, said hyperplanes having at least two dimensions and obeying an equation - View Dependent Claims (17, 18, 19, 20)
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21. A computer program product for analyzing data for biclusters, the computer program product comprising:
- a storage medium readable by a computer and storing instructions for execution by the computer for performing a method comprising;
transforming said data into parameter space using a transform, detecting hyperplanes in said data, said hyperplanes having at least two dimensions, determining whether the detected hyperplanes represent biclusters in the data, and outputting biclusters located thereby,wherein the determining comprises determining if the detected hyperplanes correspond to one or more biclusters selected from a group consisting of;
constant biclusters, constant rows, constant columns, coherent values with additive model, coherent values with multiplicative model whereby each row or column can be obtained by multiplying another row or column by a constant value, and coherent values on columns with linear model whereby each column may be obtained by multiplying another column by a constant value and then adding a constant.- View Dependent Claims (22, 23)
- a storage medium readable by a computer and storing instructions for execution by the computer for performing a method comprising;
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24. A method of data mining for biclusters in data at least partially using a processor in communication with a memory storing instructions for execution by the processor to perform the method, the method comprising detecting hyperplanes in said data, said hyperplanes having at least two dimensions, determining whether the hyperplanes represent biclusters in the data, and outputting the determined biclusters, wherein detecting hyperplanes in said data comprises transforming the data into parameter space by applying a transform to the data;
- and wherein the biclusters are coherent values with additive model whereby each row or column can be obtained by adding a constant to another row or column, or coherent values with multiplicative model whereby each row or column can be obtained by multiplying another row or column by a constant value, or coherent values on columns with linear model whereby each column may be obtained by multiplying another column by a constant value and then adding a constant.
Specification