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Spatial patterns of gene expression ...

Harmon, Cyrus Leben.

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Spatial patterns of gene expression in Drosophila melanogaster imaginal discs.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Spatial patterns of gene expression in Drosophila melanogaster imaginal discs./
Author:	Harmon, Cyrus Leben.
Description:	134 p.
Notes:	Adviser: Gerald M. Rubin.
Contained By:	Dissertation Abstracts International68-08B.
Subject:	Biology, Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3275440
ISBN:	9780549168256

Spatial patterns of gene expression in Drosophila melanogaster imaginal discs.
Harmon, Cyrus Leben.

Spatial patterns of gene expression in Drosophila melanogaster imaginal discs. - 134 p.

Adviser: Gerald M. Rubin.

Thesis (Ph.D.)--University of California, Berkeley, 2007.

We present methods and tools for the generation and analysis of large numbers of spatial patterns of gene expression in a model organism, Drosophila melanogaster. We have adopted the high-throughput probe generation and staining protocol used in the generation of gene expression patterns in Drosophila embryos to work with mass-isolated third instar larval imaginal discs and have generated patterns for over 130 different genes. We have developed methods for the automated identification, representation and characterization of these patterns using computer vision methods. We manually segmented a small number of shapes from background for each imaginal disc class and used a method known as congealing [1, 2] to automatically learn the shape of distinct classes of imaginal discs from the data [3]. We have developed methods for the automatic extraction of stain patterns, corrected for the alignment to the learned shape model. These shapes were then used as the models for a parametric alignment procedure that automatically extracts and aligns an imaginal disc shape from an image. We explored simple approaches for the clustering and classification of these patterns. We have developed libraries for matrix and image representation and processing in Common Lisp, including efficient implementations of congealing, chamfer matching and parametric alignment. Using these tools, we have developed an integrated, automated pipeline for analyzing gene expression data to select genes for spatial expression analysis, processing image data to learn imaginal disc shapes, to automatically extract instances of these learned shapes in images, to determine the spatial expression pattern of these genes in the registered images and to compare and classify these genes based on their global gene expression profile in Drosophila development and their spatial expression pattern in imaginal discs.

ISBN: 9780549168256Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Spatial patterns of gene expression in Drosophila melanogaster imaginal discs.
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035 $a (UMI)AAI3275440
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100 1 $a Harmon, Cyrus Leben. $3 1286557
245 1 0 $a Spatial patterns of gene expression in Drosophila melanogaster imaginal discs.
300 $a 134 p.
500 $a Adviser: Gerald M. Rubin.
500 $a Source: Dissertation Abstracts International, Volume: 68-08, Section: B, page: 4973.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2007.
520 $a We present methods and tools for the generation and analysis of large numbers of spatial patterns of gene expression in a model organism, Drosophila melanogaster. We have adopted the high-throughput probe generation and staining protocol used in the generation of gene expression patterns in Drosophila embryos to work with mass-isolated third instar larval imaginal discs and have generated patterns for over 130 different genes. We have developed methods for the automated identification, representation and characterization of these patterns using computer vision methods. We manually segmented a small number of shapes from background for each imaginal disc class and used a method known as congealing [1, 2] to automatically learn the shape of distinct classes of imaginal discs from the data [3]. We have developed methods for the automatic extraction of stain patterns, corrected for the alignment to the learned shape model. These shapes were then used as the models for a parametric alignment procedure that automatically extracts and aligns an imaginal disc shape from an image. We explored simple approaches for the clustering and classification of these patterns. We have developed libraries for matrix and image representation and processing in Common Lisp, including efficient implementations of congealing, chamfer matching and parametric alignment. Using these tools, we have developed an integrated, automated pipeline for analyzing gene expression data to select genes for spatial expression analysis, processing image data to learn imaginal disc shapes, to automatically extract instances of these learned shapes in images, to determine the spatial expression pattern of these genes in the registered images and to compare and classify these genes based on their global gene expression profile in Drosophila development and their spatial expression pattern in imaginal discs.
590 $a School code: 0028.
650 4 $a Biology, Bioinformatics. $3 1018415
650 4 $a Biology, Genetics. $3 1017730
650 4 $a Computer Science. $3 626642
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690 $a 0715
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710 2 $a University of California, Berkeley. $3 687832
773 0 $t Dissertation Abstracts International $g 68-08B.
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790 1 0 $a Rubin, Gerald M., $e advisor
791 $a Ph.D.
792 $a 2007
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