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.Book Part Citation - Scopus: 20Experimental MicroRNA Detection Methods(Humana Press, 2022) Yaylak, Bilge; Akgül, BünyaminMicroRNAs (miRNAs) are considerably small yet highly important riboregulators involved in nearly all cellular processes. Due to their critical roles in posttranscriptional regulation of gene expression, they have the potential to be used as biomarkers in addition to their use as drug targets. Although computational approaches speed up the initial genomewide identification of putative miRNAs, experimental approaches are essential for further validation and functional analyses of differentially expressed miRNAs. Therefore, sensitive, specific, and cost-effective microRNA detection methods are imperative for both individual and multiplex analysis of miRNA expression in different tissues and during different developmental stages. There are a number of well-established miRNA detection methods that can be exploited depending on the comprehensiveness of the study (individual miRNA versus multiplex analysis), the availability of the sample and the location and intracellular concentration of miRNAs. This review aims to highlight not only traditional but also novel strategies that are widely used in experimental identification and quantification of microRNAs. © 2022, Springer Science+Business Media, LLC, part of Springer Nature.Article Citation - WoS: 4Citation - Scopus: 12Existing Bioinformatics Tools for the Quantitation of Post-Translational Modifications(Springer Verlag, 2012) Allmer, JensMass spectrometry (MS)-based proteomics, by itself, is a vast and complex area encompassing various mass spectrometers, different spectra, and search result representations. When the aim is quantitation performed in different scanning modes at different MS levels, matters become additionally complex. Quantitation of post-translational modifications (PTM) represents the greatest challenge among these endeavors. Many different approaches to quantitation have been described and some of these can be directly applied to the quantitation of PTMs. The amount of data produced via MS, however, makes manual data interpretation impractical. Therefore, specialized software tools meet this challenge. Any software currently able to quantitate differentially labeled samples may theoretically be adapted to quantitate differential PTM expression among samples as well. Due to the heterogeneity of mass spectrometry-based proteomics; this review will focus on quantitation of PTM using liquid chromatography followed by one or more stages of mass spectrometry. Currently available free software, which either allow analysis of PTM or are easily adaptable for this purpose, is briefly reviewed in this paper. Selected studies, especially those related to phosphoproteomics, shall be used to highlight the current ability to quantitate PTMs. © Springer-Verlag 2010Article Citation - WoS: 1Citation - Scopus: 2Label-Free Quantitation, an Extension To 2db(Springer Verlag, 2010) Allmer, JensDetermining the differential expression of proteins under different conditions is of major importance in proteomics. Since mass spectrometry-based proteomics is often used to quantify proteins, several labelling strategies have been developed. While these are generally more precise than label-free quantitation approaches, they imply specifically designed experiments which also require knowledge about peptides that are expected to be measured and need to be modified. We recently designed the 2DB database which aids storage, analysis, and publication of data from mass spectrometric experiments to identify proteins. This database can aid identifying peptides which can be used for quantitation. Here an extension to the database application, named MSMAG, is presented which allows for more detailed analysis of the distribution of peptides and their associated proteins over the fractions of an experiment. Furthermore, given several biological samples in the database, label-free quantitation can be performed. Thus, interesting proteins, which may warrant further investigation, can be identified en passant while performing high-throughput proteomics studies. © 2009 Springer-Verlag.