Genes expression level quantification using a spot-based algorithmic pipeline

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Technological Educational Institute of Athens
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2007 (EN)
Genes expression level quantification using a spot-based algorithmic pipeline (EN)

Δασκαλάκης, Αντώνης (EL)
Μπουγιούκος, Παναγιώτης (EL)
Κάβουρας, Διονύσης Α. (EL)
Κωστόπουλος, Σπυρίδων (EL)
Γεωργιάδης, Παντελής (EL)

Νικηφορίδης, Γεώργιος Σ. (EL)
Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε. (EL)
Καλατζής, Ιωάννης (EL)
Καγκάδης, Γεώργιος Χ. (EL)

An efficient spot-based (SB) algorithmic pipeline of clustering, enhancement, and segmentation techniques was developed to quantify gene expression levels in microarray images. The SB-pipeline employed i/a griding procedure to locate spot-regions, ii/a clustering algorithm (enhanced fuzzy c- means or EnFCM) to roughly segment spots from background and estimate background noise and spot's center, iii/an adaptive histogram modification technique to accentuate spot's boundaries, and iv/a segmentation algorithm (Seeded Region Growing or SRG), to extract microarray spots' intensities. Extracted intensities were comparatively evaluated in term of Mean Absolute Error (MAE) against the MAGIC TOOL's SRG employing a dataset of 7 replicated microarray images (6400 spots each). MAE box-plots mean values were 0.254 and 0.630 for the SB-pipeline and the MAGIC TOOL respectively. Total processing times for the dataset evaluated (7 images) were 2100 seconds and 3410 seconds for the SB-pipeline and MAGIC TOOL respectively. (EN)

full paper

Microarray images (EN)
Gene (EN)
Εικόνες μικροσυστοιχιών (EN)
Γονίδιο (EN)

ΤΕΙ Αθήνας (EL)
Technological Educational Institute of Athens (EN)

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EN)



DOI: 10.1109/IEMBS.2007.4352499


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