A multivariate spot filtering model for two-dimensional gel electrophoresis

@article{citeulike:2565109, abstract = {Image segmentation plays an important role in the automatic analysis of protein spots in 2-DE. Using image segments representing protein spots, the amount of protein in each segment can be quantified, and corresponding segments can be matched and compared for multiple gels. However, the common presence of image segments caused by noise and unwanted artefacts highly disturb the analysis and comparison of the gels. Common sources of such artefacts are cracks in the gel surface, fingerprints, dust and other pollutions. It would be advantageous to remove these unwanted artefacts during or after the segmentation procedure. To achieve this task a multivariate spot filtering model is developed using image segments from a gel segmentation. Parameters in the model are based on texture, shape and intensity measurements of the image segments. The model successfully managed to separate segments caused by noise, artefacts and cracks from image segments representing true protein spots. The classification method used is discriminant partial least squares regression.}, address = {Department of Chemistry, Norwegian University of Science and Technology, Trondheim, Norway}, author = {Rye, Morten B. and Alsberg, Bjørn K. }, citeulike-article-id = {2565109}, doi = {10.1002/elps.200700417}, journal = {ELECTROPHORESIS}, number = {6}, pages = {1369--1381}, posted-at = {2008-05-16 03:02:39}, priority = {2}, title = {A multivariate spot filtering model for two-dimensional gel electrophoresis}, url = {http://dx.doi.org/10.1002/elps.200700417}, volume = {29}, year = {2008} }

TY - JOUR ID - citeulike:2565109 L3 - citeulike-article-id:2565109 TI - A multivariate spot filtering model for two-dimensional gel electrophoresis JF - ELECTROPHORESIS VL - 29 IS - 6 SP - 1369 EP - 1381 AD - Department of Chemistry, Norwegian University of Science and Technology, Trondheim, Norway N2 - Image segmentation plays an important role in the automatic analysis of protein spots in 2-DE. Using image segments representing protein spots, the amount of protein in each segment can be quantified, and corresponding segments can be matched and compared for multiple gels. However, the common presence of image segments caused by noise and unwanted artefacts highly disturb the analysis and comparison of the gels. Common sources of such artefacts are cracks in the gel surface, fingerprints, dust and other pollutions. It would be advantageous to remove these unwanted artefacts during or after the segmentation procedure. To achieve this task a multivariate spot filtering model is developed using image segments from a gel segmentation. Parameters in the model are based on texture, shape and intensity measurements of the image segments. The model successfully managed to separate segments caused by noise, artefacts and cracks from image segments representing true protein spots. The classification method used is discriminant partial least squares regression. AU - Rye, Morten AU - Alsberg, Bjørn PY - 2008/// UR - http://dx.doi.org/10.1002/elps.200700417 ER -