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Title: Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction. Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.
Authors:
; ; ;
Publication Date:
OSTI Identifier:
1198034
Grant/Contract Number:
DEAC05-00OR22725
Type:
Published Article
Journal Name:
International Journal of Biomedical Imaging (Print)
Additional Journal Information:
Journal Name: International Journal of Biomedical Imaging (Print); Journal Volume: 2006; Related Information: CHORUS Timestamp: 2016-08-11 12:06:59; Journal ID: ISSN 1687-4188
Publisher:
Hindawi Publishing Corporation
Sponsoring Org:
USDOE
Country of Publication:
France
Language:
English