Proteomics has gained a wide interest in the last decade since it involves the comparative study of protein expressions to identify bio-markers for early diagnosis of unpredictable, and serious, pathologies. The most powerful techniques for protein investigation compare 2D gel electrophoresys images that represent the protein composition of healthy and diseased tissues. Nevertheless, this analysis is problematic since gel images are affected by high noise levels and they are distorted, so that the same protein spot has different locations on different gels. Furthermore, the acquisition of a statistically significant sample of gels from a unique laboratory is problematic due to ethical problems, to the rarity of certain diseases, and to the fact that the process of gel electrophoresys is time consuming and costly. However, a great deal of information is present in the scientific literature in the form of images reporting 2D gels acquired for different experiments, we have developed a framework to compare annotated 2D gel images extracted from state of the art, and publicly available papers. The system has been assessed by performing the comparative analysis of the Haptoglobin; although the analyzed images are much more noisy and distorted than their sources the system achieves promising results.

Automatic Alignment of Gel 2D Images / A. Rozza, S. Arca, E. Casiraghi, P. Campadelli, M. Natale, E. Bucci, P. Consoli (FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS). - In: Neural nets wirn11 : proceedings of the 21st italian workshop on neural nets / [a cura di] B. Apolloni, S. Bassis, A. Esposito, F.C. Morabito. - Washington : IOS press, 2011 Jun 03. - ISBN 9781607509714. - pp. 3-10 (( Intervento presentato al 21. convegno Italian Workshop on neural networks : WIRN tenutosi a Vietri sul Mare (Salerno) nel 2011.

Automatic Alignment of Gel 2D Images

A. Rozza;S. Arca;E. Casiraghi;P. Campadelli;
2011

Abstract

Proteomics has gained a wide interest in the last decade since it involves the comparative study of protein expressions to identify bio-markers for early diagnosis of unpredictable, and serious, pathologies. The most powerful techniques for protein investigation compare 2D gel electrophoresys images that represent the protein composition of healthy and diseased tissues. Nevertheless, this analysis is problematic since gel images are affected by high noise levels and they are distorted, so that the same protein spot has different locations on different gels. Furthermore, the acquisition of a statistically significant sample of gels from a unique laboratory is problematic due to ethical problems, to the rarity of certain diseases, and to the fact that the process of gel electrophoresys is time consuming and costly. However, a great deal of information is present in the scientific literature in the form of images reporting 2D gels acquired for different experiments, we have developed a framework to compare annotated 2D gel images extracted from state of the art, and publicly available papers. The system has been assessed by performing the comparative analysis of the Haptoglobin; although the analyzed images are much more noisy and distorted than their sources the system achieves promising results.
image segmentation ; image denoising ; deformable template ; gel2D images
Settore INF/01 - Informatica
Settore BIO/11 - Biologia Molecolare
3-giu-2011
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/202960
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