Literature DB >> 21118235

Multiscale iterative voting for differential analysis of stress response for 2D and 3D cell culture models.

J Han1, H Chang, Q Yang, G Fontenay, T Groesser, M Helen Barcellos-Hoff, B Parvin.   

Abstract

Three-dimensional (2D) cell culture models have emerged as the basis for improved cell systems biology. However, there is a gap in robust computational techniques for segmentation of these model systems that are imaged through confocal or deconvolution microscopy. The main issues are the volume of data, overlapping subcellular compartments and variation in scale or size of subcompartments of interest, which lead to ambiguities for quantitative analysis on a cell-by-cell basis. We address these ambiguities through a series of geometric operations that constrain the problem through iterative voting and decomposition strategies. The main contributions of this paper are to (i) extend the previously developed 2D radial voting to an efficient 3D implementation, (ii) demonstrate application of iterative radial voting at multiple subcellular and molecular scales, and (iii) investigate application of the proposed technology to two endpoints between 2D and 3D cell culture models. These endpoints correspond to kinetics of DNA damage repair as measured by phosphorylation of γH2AX, and the loss of the membrane-bound E-cadherin protein as a result of ionizing radiation. Preliminary results indicate little difference in the kinetics of the DNA damage protein between 2D and 3D cell culture models; however, differences between membrane-bound E-cadherin are more pronounced.
© 2010 The Authors Journal of Microscopy © 2010 The Royal Microscopical Society.

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Mesh:

Year:  2010        PMID: 21118235     DOI: 10.1111/j.1365-2818.2010.03442.x

Source DB:  PubMed          Journal:  J Microsc        ISSN: 0022-2720            Impact factor:   1.758


  12 in total

1.  VOTING-BASED SEGMENTATION OF OVERLAPPING NUCLEI IN CLARITY IMAGES.

Authors:  Benjamin Quachtran; Luis de la Torre Ubieta; Marianna Yusupova; Daniel H Geschwind; David W Shattuck
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2018-05-24

2.  Feature-Based Representation Improves Color Decomposition and Nuclear Detection Using a Convolutional Neural Network.

Authors:  Mina Khoshdeli; Bahram Parvin
Journal:  IEEE Trans Biomed Eng       Date:  2018-03       Impact factor: 4.538

3.  Rapid 3-D delineation of cell nuclei for high-content screening platforms.

Authors:  Arkadiusz Gertych; Zhaoxuan Ma; Jian Tajbakhsh; Adriana Velásquez-Vacca; Beatrice S Knudsen
Journal:  Comput Biol Med       Date:  2015-04-25       Impact factor: 4.589

4.  Overexpression of CD36 in mammary fibroblasts suppresses colony growth in breast cancer cell lines.

Authors:  Qingsu Cheng; Kosar Jabbari; Garrett Winkelmaier; Cody Andersen; Paul Yaswen; Mina Khoshdeli; Bahram Parvin
Journal:  Biochem Biophys Res Commun       Date:  2020-03-16       Impact factor: 3.575

5.  Morphometic analysis of TCGA glioblastoma multiforme.

Authors:  Hang Chang; Gerald V Fontenay; Ju Han; Ge Cong; Frederick L Baehner; Joe W Gray; Paul T Spellman; Bahram Parvin
Journal:  BMC Bioinformatics       Date:  2011-12-20       Impact factor: 3.169

6.  AF-DHNN: Fuzzy Clustering and Inference-Based Node Fault Diagnosis Method for Fire Detection.

Authors:  Shan Jin; Wen Cui; Zhigang Jin; Ying Wang
Journal:  Sensors (Basel)       Date:  2015-07-17       Impact factor: 3.576

7.  Improved and robust detection of cell nuclei from four dimensional fluorescence images.

Authors:  Md Khayrul Bashar; Kazuo Yamagata; Tetsuya J Kobayashi
Journal:  PLoS One       Date:  2014-07-14       Impact factor: 3.240

8.  Inference of causal networks from time-varying transcriptome data via sparse coding.

Authors:  Kai Zhang; Ju Han; Torsten Groesser; Gerald Fontenay; Bahram Parvin
Journal:  PLoS One       Date:  2012-08-20       Impact factor: 3.240

9.  Integrated profiling of three dimensional cell culture models and 3D microscopy.

Authors:  Cemal Cagatay Bilgin; Sun Kim; Elle Leung; Hang Chang; Bahram Parvin
Journal:  Bioinformatics       Date:  2013-09-16       Impact factor: 6.937

10.  CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

Authors:  Erlend Hodneland; Tanja Kögel; Dominik Michael Frei; Hans-Hermann Gerdes; Arvid Lundervold
Journal:  Source Code Biol Med       Date:  2013-08-09
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