Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik
Permanent URI for this collectionhttps://hdl.handle.net/11147/9
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Book Part Citation - Scopus: 1Automated Analysis of Phase-Contrast Optical Microscopy Time-Lapse Images: Application To Wound Healing and Cell Motility Assays of Breast Cancer(Elsevier, 2023) Erdem, Yusuf Sait; Ayanzadeh, Aydın; Mayalı, Berkay; Balıkçı, Muhammed; Belli, Özge Nur; Uçar, Mahmut; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Önal, Sevgi; Morani, Kenan; Iheme, Leonardo Obinna; Töreyin, Behçet UğurThis chapter describes a workflow for analyzing phase-contrast microscopy (PCM) data from two fundamental types of biomedical assays: assays for cell motility and assays for wound healing. The workflow of the analysis is composed of the methods for acquiring, restoring, segmenting, and quantifying biomedical data. In the literature, there have been separate methods aimed at specific stages of PCM data analysis. Nonetheless, there has never been a complete workflow for all stages of analysis. This work is an innovation that proposes an end-to-end workflow for image pre-processing, deep learning segmentation, tracking, and quantification stages in cell motility and wound healing assay analyses. The findings indicate that domain knowledge can be used to make simple but significant improvements to the results of cutting-edge methods. Furthermore, even for deep learning-based methods, pre-processing is clearly a necessary step in the workflow. © 2023 Elsevier Inc. All rights reserved.Article Citation - WoS: 246Citation - Scopus: 245Step-By Quantitative Analysis of Focal Adhesions(Elsevier Ltd., 2014) Horzum, Utku; Özdil, Berrin; Pesen Okvur, DevrimFocal adhesions (FAs) are specialized adhesive structures which serve as cellular communication units between cells and the surrounding extracellular matrix. FAs are involved in signal transduction and actin cytoskeleton organization. FAs mediate cell adhesion, which is a critical phenomenon in cancer research. Since cells can form many and micrometer scale FAs, their quantitative analysis demands well-optimized image analysis approaches [1-3]. Here, we have optimized the analysis of FAs of MDA-MB-231 breast cancer cells. The optimization is based on proper processing of immunofluorescence images of vinculin, which is one of the markers of FAs. All image processing steps are carried out using the ImageJ software, which is freely available and in the public domain. The advantages of our method are:The analysis steps are simplified by combining different plugins of the ImageJ program.FAs are better detected with minimal false negatives due to optimized processing of fluorescent images.This approach can be applied to quantify a variety of fluorescent images comprising focal and/or localized signals within a high background such as FAs, one of the many complex signaling structures in a cell.
