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Microarray subgrid detection: a novel algorithm
2007
International Journal of Computer Mathematics
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In this paper, a novel algorithm for detecting microarray sub-grids is proposed. ...
The only input to the proposed algorithm is the raw microarray image, which can be at any resolution, and the subgrid detection is performed with no prior assumptions. ...
A novel algorithm is proposed which consists of a series of methods including; spot shape detection, spot filtering, spot spacing estimation, subgrid shape detection and finally sub-grid detection. ...
doi:10.1080/00207160701242292
fatcat:vye3ludu7zf5xpt6qrln7s6ceu
Sub-grid and Spot Detection in DNA Microarray Images Using Optimal Multi-level Thresholding
[chapter]
2010
Lecture Notes in Computer Science
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We propose a fully automatic approach that first detects the sub-grids given the entire microarray image, and then detects the locations of the spots in each sub-grid. ...
The approach first detects and corrects rotations in the images by an affine transformation, followed by a polynomial-time optimal multi-level thresholding algorithm to find the positions of the sub-grids ...
Conclusions A novel method for separating sub-grids and spot centers in cDNA microarray images has been proposed. ...
doi:10.1007/978-3-642-16001-1_24
fatcat:jpf6bttxrncpresv4vahvy4wwa
A Fully Automated Gridding Technique for Real Composite cDNA Microarray Images
2020
IEEE Access
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Miguel Hernandez-Cabronero, the Postdoctoral Research Assistant at 'Universitat Autonoma de Barcelona' (UAB), Spain for providing the microarray image database 1 (SIB) and database 4 (SMD) for the evaluation ...
Automatic gridding algorithms detect all spots of microarray images without any preset parameters or user intervention. ...
Our work employs a novel preprocessing method which gives a good contrast with reduced noise effect on highdensity noisy images. ...
doi:10.1109/access.2020.2975855
fatcat:dv3rgewrhrbh5dzub5ib3r2oti
Hybrid Spot Segmentation in Four-Channel Microarray Genotyping Image Data
2006
2006 IEEE International Symposium on Signal Processing and Information Technology
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In this paper we present a novel hybrid algorithm for spot segmentation in four-channel genotyping microarray images. ...
A spatial shape detection step is simultaneously applied, which assists a nonlinear diffusion filtering step in detecting the connected objects, while a spot masking step prevents various noise types from ...
Our grids are composed of 16 subgrids in a 4 × 4 arrangement. Each subgrid is an 18 × 18 arrangement of spots. Figure 1 also shows a subgrid, and a cell containing an individual spot. ...
doi:10.1109/isspit.2006.270761
fatcat:wgugvbczxbbitfsb7dqfk6ov4e
Detection of tmRNA molecules on microarrays at low temperatures using helper oligonucleotides
2010
BMC Biotechnology
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The hybridization of synthetic Streptococcus pneumoniae tmRNA on a detection microarray is slow at 34°C resulting in low signal intensities. ...
Results: We demonstrate that adding specific DNA helper oligonucleotides (chaperones) to the hybridization buffer increases the signal strength at a given temperature and thus makes the specific detection ...
In addition, a practical use for chaperones as a interesting novel tool in secondary structure analysis was demonstrated. ...
doi:10.1186/1472-6750-10-34
pmid:20426847
pmcid:PMC2873282
fatcat:2ippbk23q5gqlkb2uisxya6kcy
An Overview of DNA Microarray Grid Alignment and Foreground Separation Approaches
2006
EURASIP Journal on Advances in Signal Processing
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We present several classifications of existing algorithms, and describe the fundamental principles of these algorithms. ...
Thus, understanding microarray data processing steps becomes critical for performing optimal microarray data analysis. ...
Figure 4 illustrates 1D projections derived from a preprocessed image by Sobel edge detection algorithm [41] . ...
doi:10.1155/asp/2006/80163
fatcat:ennacwyq5jdpvmfpuzep7a6vzy
A novel neural network approach to cDNA microarray image segmentation
2013
Computer Methods and Programs in Biomedicine
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Microarray images typically contain several thousands of small spots, each of which represents a different gene in the experiment. ...
Microarray technology has become a great source of information for biologists to understand the workings of DNA which is one of the most complex codes in nature. ...
As such, in this paper, we aim to propose a novel method segmenting microarray images with hope to produce results that are as good as, if not better than, the results of most advanced microarray segmentation ...
doi:10.1016/j.cmpb.2013.03.013
pmid:23669179
fatcat:o2yw2juwu5f23gbukazvn3up2a
MACE
2006
Proceedings of the 2006 ACM symposium on Applied computing - SAC '06
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In this paper, we propose a conceptually novel approach that achieves significantly better lossless compression. ...
We have also developed a software application called MACE (Microarray Compression and Extraction application) to compress-decompress microarray data and generate the aforementioned format. ...
Jonathan Pollack, of the Pollack Lab and Janos Demeter, the Microarray Curator, both of Stanford University for their valuable assistance in providing sample microarray images. ...
doi:10.1145/1141277.1141315
dblp:conf/sac/BiermanMPS06
fatcat:6yiivnxftfcuvposyuvfmag2v4
Adaptive techniques for microarray image analysis with related quality assessment
2007
Journal of Electronic Imaging (JEI)
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We propose the microarray image rotation algorithm (MIRA) and the statistical gridding pipeline (SGRIP) as two advanced modules devoted to restoring the original microarray grid orientation and to detecting ...
We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. ...
In this paper we introduce a novel algorithm, the microarray image rotation algorithm ͑MIRA͒, to take into account typical rotation problems of microarray images. ...
doi:10.1117/1.2816445
fatcat:6tnpohtl6rhnjdnogbeae3vwvi
Automatic DNA microarray gridding based on Support Vector Machines
2008
2008 8th IEEE International Conference on BioInformatics and BioEngineering
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This paper presents a novel method for DNA microarray gridding based on Support Vector Machine (SVM) classifiers. ...
It employs a set of soft-margin SVMs to estimate the lines of the DNA microarray grid by maximizing the margin between the lines and the spots. ...
Fig. 1 . 1 Gridding algorithm steps: (a) original image, (b) normalization, (c) edge-detection, (d) thresholding, (e) spot detection, (f) valid spots, (g) rows and columns of spots, (h) SVM-
θ=15°θ=15 ...
doi:10.1109/bibe.2008.4696795
dblp:conf/bibe/BariamisMI08
fatcat:flghthlqtzh2fazucibyur3lbq
An Automatic Gridding And Contour Based Segmentation Approach Applied To Dna Microarray Image Analysis
2008
Zenodo
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In this paper, a tool to perform DNA microarray image analysis is presented, including a spot addressing method based on the image projections, the spot segmentation through contour based segmentation ...
DNA microarray technology is widely used by geneticists to diagnose or treat diseases through gene expression. ...
By applying a local minima detection algorithm to the vectors created, the positions for the lines of the arrays can be specified. ...
doi:10.5281/zenodo.1081549
fatcat:zhfu7txqcjdbnf64qsc44e3zvi
Characterization of Gene Expression Profiles of Normal Canine Retina and Brain Using a Retinal cDNA Microarray
[chapter]
2008
Advances in Experimental Medicine and Biology
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Each sample was studied against a reference sample of pooled brain RNA. Data from a quantified scanned image were normalized using the loess subgrid procedure. ...
Retina-enriched genes were identified using the Significance Analysis of Microarrays (SAM) algorithm, and confirmed by northern blot analyses for selected genes. ...
ACKNOWLEDGEMENTS We would like to acknowledge Don A. ...
doi:10.1007/978-0-387-74904-4_20
pmid:18188943
fatcat:gjlupob3drgvdlavrbhlulcnpi
Chromosomal Localization of DNA Amplifications in Neuroblastoma Tumors Using cDNA Microarray Comparative Genomic Hybridization
2003
Neoplasia: An International Journal for Oncology Research
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Cluster analysis of microarray CGH data identified three groups: 1 ) no amplifications evident, 2 ) a small MYCN amplicon as the only detectable imbalance, and 3 ) a large MYCN amplicon with additional ...
A dedicated ( freely available ) algorithm was developed for rapid in silico determination of chromosomal localizations of microarray cDNA targets, and for generation of an ideogram -type profile of copy ...
The features of the 19k2 microarray are arranged on two glass slides ( parts A and B ), each with 32 subgrids spotted over an approximate area of 18Â36 mm 2 . ...
doi:10.1016/s1476-5586(03)80017-9
pmid:12659670
pmcid:PMC1502121
fatcat:hxndnyd3rnedpcc5vjx7tp5tpq
Comparison of comparative genomic hybridization technologies across microarray platforms
2009
Journal of Biomolecular Techniques
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In the HL-60 genome, at least two of the five platforms detected five novel losses and five novel gains. ...
In the 2007 Association of Biomolecular Resource Facilities Microarray Research Group project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and ...
It also includes a novel arrayCGH platform using an RNA expression microarray to detect DNA copy number variation. 1 Using both platform-specific analyses and a common CBS approach, we found that all ...
pmid:19503625
pmcid:PMC2685605
fatcat:ey7pcurswrhu7ni4acl2ylsfb4
Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB
2009
BMC Bioinformatics
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The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. ...
This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. ...
Acknowledgements The authors want to express their acknowledgements to Dr Vassilis Aidinis for his heedful remarks concerning the evaluation of the performance of the Gene ARMADA algorithms and Dr Olga ...
doi:10.1186/1471-2105-10-354
pmid:19860866
pmcid:PMC2771024
fatcat:yhh4cqcbprcebb3qcfvmgabrpe
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