Apparatus and method for classifying multi-dimensional biological data
First Claim
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1. A method of identifying a biological activity of a compound of interest, comprising:
- providing a plurality of gene expression datasets associated with a first class of compounds having a first biological activity;
providing a plurality of gene expression datasets associated with a second class of compounds having a second biological activity;
deriving a linear classification rule based on said plurality of gene expression datasets; and
applying said linear classification rule to a set of gene expression levels associated with said compound of interest thereby determining whether said compound of interest has said first biological activity or said second biological activity.
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Abstract
Apparatus and method for classifying multi-dimensional biological data are described. In some embodiments, a methodology for deriving a linear classification rule can be used for predicting a biological activity or a biological state. Advantageously, the methodology described herein facilitates obtaining robust and sparse classifiers that account for uncertainty involved in real-world experiments and improve computational efficiency and ease of interpretation of results.
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19 Claims
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1. A method of identifying a biological activity of a compound of interest, comprising:
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providing a plurality of gene expression datasets associated with a first class of compounds having a first biological activity;
providing a plurality of gene expression datasets associated with a second class of compounds having a second biological activity;
deriving a linear classification rule based on said plurality of gene expression datasets; and
applying said linear classification rule to a set of gene expression levels associated with said compound of interest thereby determining whether said compound of interest has said first biological activity or said second biological activity. - View Dependent Claims (2, 3, 4, 5, 6, 7, 12)
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8. A method of identifying a biological state of a biological sample, comprising:
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providing a plurality of gene expression datasets, each gene expression dataset of said plurality of gene expression datasets including a set of gene expression levels and a set of gene expression intervals, said plurality of gene expression datasets including a first plurality of gene expression datasets associated with a first biological state and a second plurality of gene expression datasets associated with a second biological state;
deriving a linear classification rule based on said plurality of gene expression datasets; and
applying said linear classification rule to a set of gene expression levels associated with said biological sample to identify a biological state of said biological sample as one of said first biological state and said second biological state. - View Dependent Claims (9, 10, 11, 13, 14)
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15. A method for classifying a test gene expression dataset comprising:
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providing a reference gene expression dataset;
deriving a linear classification rule by reducing the value of a loss function associated with said reference gene expression dataset; and
applying said linear classification rule to a test gene expression dataset thereby determining the classification of the test gene expression dataset. - View Dependent Claims (16, 17)
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18. A computer program product for classifying a test gene expression dataset comprising:
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computer code for querying a reference gene expression dataset;
computer code for deriving a linear classification rule by reducing the value of a loss function associated with said reference gene expression dataset;
computer code for applying said linear classification rule to a test gene expression dataset and thereby determining the classification of the test gene expression dataset; and
computer code for outputting the test dataset classification to the user. - View Dependent Claims (19)
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Specification