1.1 --- a/grant.html Tue Apr 21 05:34:25 2009 -0700 1.2 +++ b/grant.html Tue Apr 21 05:38:52 2009 -0700 1.3 @@ -660,36 +660,33 @@ 1.4 structure in the gene expression data led to any unexpected or interesting features of these maps. 1.5 Timeline and milestones 1.6 Aim 1 1.7 -∙Oct-Nov 2009: develop an automated mechanism for segmenting the cortical voxels into layers 1.8 -∙Nov 2009 (milestone): a preliminary automated mechanism for segmenting the cortical voxels into layers 1.9 -∙Oct 2009-Feb 2010: develop scoring methods and to test them in various supervised learning frameworks. Also test 1.10 -out various dimensionality reduction schemes in combination with supervised learning. 1.11 -∙Dec 2009-April 2010: create or extend supervised learning frameworks which use multivariate versions of the best 1.12 -scoring methods 1.13 +∙October-November 2009: develop an automated mechanism for segmenting the cortical voxels into layers 1.14 +∙November 2009 (milestone): a preliminary automated mechanism for segmenting the cortical voxels into layers 1.15 +∙October 2009-April 2010: develop scoring methods and to test them in various supervised learning frameworks. Also 1.16 +test out various dimensionality reduction schemes in combination with supervised learning. create or extend supervised 1.17 +learning frameworks which use multivariate versions of the best scoring methods. 1.18 ∙January 2010 (milestone): submit a publication on single marker genes for cortical areas 1.19 -∙February-June 2010: explore the best way to integrate radial profiles with supervised learning. Explore the best way 1.20 -to make supervised learning techniques robust against incorrect labels (i.e. when the areas drawn on the input cortical 1.21 -map are slightly off). Quantitatively compare the performance of different supervised learning techniques. 1.22 -∙May-July 2010: Validate marker genes found in the ABA dataset by checking against other gene expression datasets 1.23 -∙June 2010: submit a paper describing a method fulfilling Aim 1 1.24 -∙July 2010: submit a paper describing combinations of marker genes for each cortical area, and a small number of 1.25 -marker genes that can, in combination, define most of the areas at once 1.26 -∙April-July 2010: create documentation and unit tests for software toolbox for Aim 1. 1.27 -∙August 2010-: respond to user bug reports for Aim 1 software toolbox. 1.28 +∙February-July 2010: Continue to develop scoring methods and supervised learning frameworks. Explore the best way 1.29 +to integrate radial profiles with supervised learning. Explore the best way to make supervised learning techniques 1.30 +robust against incorrect labels (i.e. when the areas drawn on the input cortical map are slightly off). Quantitatively 1.31 +compare the performance of different supervised learning techniques. Validate marker genes found in the ABA dataset 1.32 +by checking against other gene expression datasets. Create documentation and unit tests for software toolbox for Aim 1.33 +1. Respond to user bug reports for Aim 1 software toolbox. 1.34 +∙June 2010 (milestone): submit a paper describing a method fulfilling Aim 1. Release toolbox. 1.35 +∙July 2010 (milestone): submit a paper describing combinations of marker genes for each cortical area, and a small 1.36 +number of marker genes that can, in combination, define most of the areas at once 1.37 Aim 2 1.38 -∙April-September 2010: explore dimensionality reduction algorithms for Aim 2 1.39 -∙June-November 2010: explore standard hierarchial clustering algorithms, used in combination with dimensionality 1.40 -reduction, for Aim 2 1.41 -∙July-December 2010: explore co-clustering algorithms. Think about how radial profile information can be used for 1.42 -Aim 2. Adapt clustering algorithms to use radial profile information. 1.43 +∙April-September 2010: Explore dimensionality reduction algorithms for Aim 2. Explore standard hierarchial clus- 1.44 +tering algorithms, used in combination with dimensionality reduction, for Aim 2. Explore co-clustering algorithms. 1.45 +Think about how radial profile information can be used for Aim 2. Adapt clustering algorithms to use radial profile 1.46 +information. 1.47 ∙January-March 2011: Quantitatively compare the performance of different dimensionality reduction and clustering 1.48 techniques. Quantitatively compare the value of different flatmapping methods and ways of representing radial profiles. 1.49 -∙January-June 2011: using the methods developed for Aim 2, explore the genomic anatomy of the cortex. Read the 1.50 -literature and talk to people to learn about research related to unexpected and interesting discoveries. 1.51 -∙February-May 2011: create documentation and unit tests for software toolbox for Aim 2. 1.52 -∙June 2011-: respond to user bug reports for Aim 1 software toolbox. 1.53 -∙March 2011: submit a paper describing a method fulfilling Aim 2 1.54 -∙May 2011: submit a paper on the genomic anatomy of the cortex, using the methods developed in Aim 2 1.55 +∙March 2011 (milestone): submit a paper describing a method fulfilling Aim 2. Release toolbox. 1.56 +∙February-May 2011: Using the methods developed for Aim 2, explore the genomic anatomy of the cortex. Read 1.57 +the literature and talk to people to learn about research related to unexpected and interesting discoveries. Create 1.58 +documentation and unit tests for software toolbox for Aim 2. Respond to user bug reports for Aim 1 software toolbox. 1.59 +∙May 2011 (milestone): submit a paper on the genomic anatomy of the cortex, using the methods developed in Aim 2 1.60 ∙May-August 2011: revisit Aim 1 to see if what was learned during Aim 2 can improve the methods for Aim 1. 1.61 Bibliography & References Cited 1.62 [1]Chris Adamson, Leigh Johnston, Terrie Inder, Sandra Rees, Iven Mareels, and Gary Egan. A Tracking Approach to

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4.1 --- a/grant.txt Tue Apr 21 05:34:25 2009 -0700 4.2 +++ b/grant.txt Tue Apr 21 05:38:52 2009 -0700 4.3 @@ -535,28 +535,19 @@ 4.4 4.5 === Aim 1 === 4.6 4.7 -* Oct-Nov 2009: develop an automated mechanism for segmenting the cortical voxels into layers 4.8 -* Nov 2009 (milestone): a preliminary automated mechanism for segmenting the cortical voxels into layers 4.9 -* Oct 2009-Feb 2010: develop scoring methods and to test them in various supervised learning frameworks. Also test out various dimensionality reduction schemes in combination with supervised learning. 4.10 -* Dec 2009-April 2010: create or extend supervised learning frameworks which use multivariate versions of the best scoring methods 4.11 +* October-November 2009: develop an automated mechanism for segmenting the cortical voxels into layers 4.12 +* November 2009 (milestone): a preliminary automated mechanism for segmenting the cortical voxels into layers 4.13 +* October 2009-April 2010: develop scoring methods and to test them in various supervised learning frameworks. Also test out various dimensionality reduction schemes in combination with supervised learning. create or extend supervised learning frameworks which use multivariate versions of the best scoring methods. 4.14 * January 2010 (milestone): submit a publication on single marker genes for cortical areas 4.15 -* February-June 2010: explore the best way to integrate radial profiles with supervised learning. Explore the best way to make supervised learning techniques robust against incorrect labels (i.e. when the areas drawn on the input cortical map are slightly off). Quantitatively compare the performance of different supervised learning techniques. 4.16 -* May-July 2010: Validate marker genes found in the ABA dataset by checking against other gene expression datasets 4.17 -* June 2010: submit a paper describing a method fulfilling Aim 1 4.18 -* July 2010: submit a paper describing combinations of marker genes for each cortical area, and a small number of marker genes that can, in combination, define most of the areas at once 4.19 -* April-July 2010: create documentation and unit tests for software toolbox for Aim 1. 4.20 -* August 2010-: respond to user bug reports for Aim 1 software toolbox. 4.21 +* February-July 2010: Continue to develop scoring methods and supervised learning frameworks. Explore the best way to integrate radial profiles with supervised learning. Explore the best way to make supervised learning techniques robust against incorrect labels (i.e. when the areas drawn on the input cortical map are slightly off). Quantitatively compare the performance of different supervised learning techniques. Validate marker genes found in the ABA dataset by checking against other gene expression datasets. Create documentation and unit tests for software toolbox for Aim 1. Respond to user bug reports for Aim 1 software toolbox. 4.22 +* June 2010 (milestone): submit a paper describing a method fulfilling Aim 1. Release toolbox. 4.23 +* July 2010 (milestone): submit a paper describing combinations of marker genes for each cortical area, and a small number of marker genes that can, in combination, define most of the areas at once 4.24 4.25 === Aim 2 === 4.26 -* April-September 2010: explore dimensionality reduction algorithms for Aim 2 4.27 -* June-November 2010: explore standard hierarchial clustering algorithms, used in combination with dimensionality reduction, for Aim 2 4.28 -* July-December 2010: explore co-clustering algorithms. Think about how radial profile information can be used for Aim 2. Adapt clustering algorithms to use radial profile information. 4.29 -* January-March 2011: Quantitatively compare the performance of different dimensionality reduction and clustering techniques. Quantitatively compare the value of different flatmapping methods and ways of representing radial profiles. 4.30 -* January-June 2011: using the methods developed for Aim 2, explore the genomic anatomy of the cortex. Read the literature and talk to people to learn about research related to unexpected and interesting discoveries. 4.31 -* February-May 2011: create documentation and unit tests for software toolbox for Aim 2. 4.32 -* June 2011-: respond to user bug reports for Aim 1 software toolbox. 4.33 -* March 2011: submit a paper describing a method fulfilling Aim 2 4.34 -* May 2011: submit a paper on the genomic anatomy of the cortex, using the methods developed in Aim 2 4.35 +* April-March 2011: Explore dimensionality reduction algorithms for Aim 2. Explore standard hierarchial clustering algorithms, used in combination with dimensionality reduction, for Aim 2. Explore co-clustering algorithms. Think about how radial profile information can be used for Aim 2. Adapt clustering algorithms to use radial profile information. Quantitatively compare the performance of different dimensionality reduction and clustering techniques. Quantitatively compare the value of different flatmapping methods and ways of representing radial profiles. 4.36 +* March 2011 (milestone): submit a paper describing a method fulfilling Aim 2. Release toolbox. 4.37 +* February-May 2011: Using the methods developed for Aim 2, explore the genomic anatomy of the cortex. Read the literature and talk to people to learn about research related to unexpected and interesting discoveries. Create documentation and unit tests for software toolbox for Aim 2. Respond to user bug reports for Aim 1 software toolbox. 4.38 +* May 2011 (milestone): submit a paper on the genomic anatomy of the cortex, using the methods developed in Aim 2 4.39 * May-August 2011: revisit Aim 1 to see if what was learned during Aim 2 can improve the methods for Aim 1. 4.40 4.41 \newpage