1.1 --- a/grant.html Mon Apr 13 03:13:10 2009 -0700 1.2 +++ b/grant.html Mon Apr 13 03:15:57 2009 -0700 1.3 @@ -276,7 +276,7 @@ 1.4 gene expression data. 1.5 There is a substantial body of work on the analysis of gene expression data, 1.6 however, most of this concerns gene expression data which is not fundamentally 1.7 - spatial, for example, microarray datasets. 1.8 + spatial. 1.9 As noted above, there has been much work on both supervised learning and 1.10 clustering, and there are many available algorithms for each. However, the 1.11 completion of Aims 1 and 2 involves more than just choosing between a set of

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4.1 --- a/grant.txt Mon Apr 13 03:13:10 2009 -0700 4.2 +++ b/grant.txt Mon Apr 13 03:15:57 2009 -0700 4.3 @@ -138,7 +138,7 @@ 4.4 === Related work === 4.5 There does not appear to be much work on the automated analysis of spatial gene expression data. 4.6 4.7 -There is a substantial body of work on the analysis of gene expression data, however, most of this concerns gene expression data which is not fundamentally spatial, for example, microarray datasets. 4.8 +There is a substantial body of work on the analysis of gene expression data, however, most of this concerns gene expression data which is not fundamentally spatial. 4.9 4.10 As noted above, there has been much work on both supervised learning and clustering, and there are many available algorithms for each. However, the completion of Aims 1 and 2 involves more than just choosing between a set of existing algorithms, and will constitute a substantial contribution to biology. The algorithms require the scientist to provide a framework for representing the problem domain, and the way that this framework is set up has a large impact on performance. Creating a good framework can require creatively reconceptualizing the problem domain, and is not merely a mechanical "fine-tuning" of numerical parameters. For example, we believe that domain-specific scoring measures (such as gradient similarity, which is discussed in Preliminary Work) may be necessary in order to achieve the best results in this application. 4.11