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Carsten Peterson
Expert
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Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states
Other contributions
- Javed Khan
- Markus Ringnér
- Carsten Peterson
- Paul Meltzer
Summary, in English
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.
Department/s
- Molecular Cell Biology
- Computational Biology and Biological Physics - Has been reorganised
Publishing year
2011-11-22
Language
English
Document type
Patent
Topic
- Bioinformatics and Systems Biology
Status
Published