NDLI: A hill-climbing approach for automatic gridding of cDNA microarray images

Please wait, while we are loading the content...

A hill-climbing approach for automatic gridding of cDNA microarray images

Content Provider	IEEE Xplore Digital Library
Author	Rueda, L. Vidyadharan, V.
Copyright Year	2004
Abstract	Image and statistical analysis are two important stages of cDNA microarrays. Of these, gridding is necessary to accurately identify the location of each spot while extracting spot intensities from the microarray images and automating this procedure permits high-throughput analysis. Due to the deficiencies of the equipment used to print the arrays, rotations, misalignments, high contamination with noise and artifacts, and the enormous amount of data generated, solving the gridding problem by means of an automatic system is not trivial. Existing techniques to solve the automatic grid segmentation problem cover only limited aspects of this challenging problem and require the user to specify the size of the spots, the number of rows and columns in the grid, and boundary conditions. In this paper, a hill-climbing automatic gridding and spot quantification technique is proposed which takes a microarray image (or a subgrid) as input and makes no assumptions about the size of the spots, rows, and columns in the grid. The proposed method is based on a hill-climbing approach that utilizes different objective functions. The method has been found to effectively detect the grids on microarray images drawn from databases from GEO and the Stanford genomic laboratories
Sponsorship	IEEE Computer Society
Page Count	12
File Size	6884672
Starting Page	72
Ending Page	83
File Format	PDF
ISSN	15455963
Volume Number	3
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Statistical analysis Data mining Image analysis Contamination Noise generators Mesh generation Image segmentation Boundary conditions Image databases Genomics hill-climbing. cDNA Microarrays gene expression gridding
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Genetics Biotechnology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Using the Maximum Between-Class Variance for Automatic Gridding of cDNA Microarray Images

A Deformable Grid-Matching Approach for Microarray Images

Gridding spot centers of smoothly distorted microarray images

3-D Spot Modeling for Automatic Segmentation of cDNA Microarray Images

An Original Genetic Approach to the Fully Automatic Gridding of Microarray Images

Super Pixel based Microarray Image Analysis for Identification of Diseases

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

Correlation Statistics for cDNA Microarray Image Analysis

Analysis of cDNA microarray images

A hill-climbing approach for automatic gridding of cDNA microarray images

Similar Documents

Using the Maximum Between-Class Variance for Automatic Gridding of cDNA Microarray Images

A Deformable Grid-Matching Approach for Microarray Images

Gridding spot centers of smoothly distorted microarray images

3-D Spot Modeling for Automatic Segmentation of cDNA Microarray Images

An Original Genetic Approach to the Fully Automatic Gridding of Microarray Images

Super Pixel based Microarray Image Analysis for Identification of Diseases

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

Correlation Statistics for cDNA Microarray Image Analysis

Analysis of cDNA microarray images

A hill-climbing approach for automatic gridding of cDNA microarray images