1.1 --- a/grant.html Mon Apr 13 03:25:42 2009 -0700 1.2 +++ b/grant.html Mon Apr 13 03:31:42 2009 -0700 1.3 @@ -52,7 +52,7 @@ 1.4 gene expression dataset used in the construction of the classifier is called training 1.5 data. 1.6 In the machine learning literature, this sort of procedure may be thought 1.7 - of as a supervised learning task, defined as a task in whcih the goal is to learn 1.8 + of as a supervised learning task, defined as a task in which the goal is to learn 1.9 a mapping from instances to labels, and the training data consists of a set of 1.10 instances (voxels) for which the labels (subregions) are known. 1.11 Each gene expression level is called a feature, and the selection of which 1.12 @@ -489,6 +489,7 @@ 1.13 app2 has examples of genetic targeting to specific anatomical regions 1.14 — 1.15 note: 1.16 + do we need to cite: no known markers? impressive results? 1.17 14 1.18 1.19

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4.1 --- a/grant.txt Mon Apr 13 03:25:42 2009 -0700 4.2 +++ b/grant.txt Mon Apr 13 03:31:42 2009 -0700 4.3 @@ -29,7 +29,7 @@ 4.4 4.5 The object of aim 1 is not to produce a single classifier, but rather to develop an automated method for determining a classifier for any known anatomical structure. Therefore, we seek a procedure by which a gene expression dataset may be analyzed in concert with an anatomical atlas in order to produce a classifier. Such a procedure is a type of a machine learning procedure. The construction of the classifier is called __training__ (also __learning__), and the initial gene expression dataset used in the construction of the classifier is called __training data__. 4.6 4.7 -In the machine learning literature, this sort of procedure may be thought of as a __supervised learning task__, defined as a task in whcih the goal is to learn a mapping from instances to labels, and the training data consists of a set of instances (voxels) for which the labels (subregions) are known. 4.8 +In the machine learning literature, this sort of procedure may be thought of as a __supervised learning task__, defined as a task in which the goal is to learn a mapping from instances to labels, and the training data consists of a set of instances (voxels) for which the labels (subregions) are known. 4.9 4.10 Each gene expression level is called a __feature__, and the selection of which genes to include is called __feature selection__. Feature selection is one component of the task of learning a classifier. Some methods for learning classifiers start out with a separate feature selection phase, whereas other methods combine feature selection with other aspects of training. 4.11 4.12 @@ -316,3 +316,5 @@ 4.13 --- 4.14 4.15 note: 4.16 + 4.17 +do we need to cite: no known markers? impressive results?