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Proceedings Paper

Image analysis for DNA sequencing
Author(s): Kannappan Palaniappan; Thomas S. Huang
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Paper Abstract

There is a great deal of interest in automating the process of DNA (deoxyribonucleic acid) sequencing to support the analysis of genomic DNA such as the Human and Mouse Genome projects. In one class of gel-based sequencing protocols autoradiograph images are generated in the final step and usually require manual interpretation to reconstruct the DNA sequence represented by the image. The need to handle a large volume of sequence information necessitates automation of the manual autoradiograph reading step through image analysis in order to reduce the length of time required to obtain sequence data and reduce transcription errors. Various adaptive image enhancement, segmentation and alignment methods were applied to autoradiograph images. The methods are adaptive to the local characteristics of the image such as noise, background signal, or presence of edges. Once the two-dimensional data is converted to a set of aligned one-dimensional profiles waveform analysis is used to determine the location of each band which represents one nucleotide in the sequence. Different classification strategies including a rule-based approach are investigated to map the profile signals, augmented with the original two-dimensional image data as necessary, to textual DNA sequence information.

Paper Details

Date Published: 1 July 1991
PDF: 12 pages
Proc. SPIE 1450, Biomedical Image Processing II, (1 July 1991); doi: 10.1117/12.44310
Show Author Affiliations
Kannappan Palaniappan, Univ. of Illinois/Urbana-Champaign (United States)
Thomas S. Huang, Univ. of Illinois/Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 1450:
Biomedical Image Processing II
Alan Conrad Bovik; Vyvyan Howard, Editor(s)

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