Proteomics is the science that studies the proteome, that is the proteic expression of the genome. Cell proteome is extremely complex, and is composed of several thousand proteins. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) is widely used as a standard method to separate and display proteins in a tissue or compound with a theoretical resolution of 104 proteins simultaneously. This technique combines the resolution power of isoelectrofocalization (IEF), which distinguishes proteins by their isoelectric point (pI), with SDS-PAGE (sodium dodecyl sulphate PAGE), in which proteins are separated according to their weight and molecular size. Our group is developing software algorithms for the automatic analysis of images obtained by 2D-PAGE gel optical scanning; our aim is the reduction of human intervention in the analysis process, currently quite slow, operator-dependent, and prone to errors. In our approach, image noise is first reduced, in order to limit false positives and protein missing. Proteins appear as dark spots on a light background, so the next step is local minima search. Then, the watershed transform is applied, which partitions the gel image into basins: each basin contains a single (recognized) minimum, but can possibly include more than one protein spot if less-deep minima are masked by the main one. At this point, we perform a registration between the work image and an atlas image (already analyzed by a biologist), and map the atlas spot positions to the work image. Each basin is then used as a region of interest (ROI) in which the shape of the spot (or spots) is fit to a model through a χ2-minimization procedure. The coordinates of the transformed spots are used as the fit initialization parameters.

Integrated Models for the Analysis of Two-Dimensional Electrophoresis Gel Images

2008

Abstract

Proteomics is the science that studies the proteome, that is the proteic expression of the genome. Cell proteome is extremely complex, and is composed of several thousand proteins. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) is widely used as a standard method to separate and display proteins in a tissue or compound with a theoretical resolution of 104 proteins simultaneously. This technique combines the resolution power of isoelectrofocalization (IEF), which distinguishes proteins by their isoelectric point (pI), with SDS-PAGE (sodium dodecyl sulphate PAGE), in which proteins are separated according to their weight and molecular size. Our group is developing software algorithms for the automatic analysis of images obtained by 2D-PAGE gel optical scanning; our aim is the reduction of human intervention in the analysis process, currently quite slow, operator-dependent, and prone to errors. In our approach, image noise is first reduced, in order to limit false positives and protein missing. Proteins appear as dark spots on a light background, so the next step is local minima search. Then, the watershed transform is applied, which partitions the gel image into basins: each basin contains a single (recognized) minimum, but can possibly include more than one protein spot if less-deep minima are masked by the main one. At this point, we perform a registration between the work image and an atlas image (already analyzed by a biologist), and map the atlas spot positions to the work image. Each basin is then used as a region of interest (ROI) in which the shape of the spot (or spots) is fit to a model through a χ2-minimization procedure. The coordinates of the transformed spots are used as the fit initialization parameters.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12571/3188
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