Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Boyvat, DuduHas files: Yes

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  • Article
    Citation - WoS: 6
    Citation - Scopus: 7
    Improved Senescent Cell Segmentation on Bright-Field Microscopy Images Exploiting Representation Level Contrastive Learning
    (Wiley, 2024) Celebi, Fatma; Boyvat, Dudu; Ayaz-Guner, Serife; Tasdemir, Kasim; Icoz, Kutay
    Mesenchymal stem cells (MSCs) are stromal cells which have multi-lineage differentiation and self-renewal potentials. Accurate estimation of total number of senescent cells in MSCs is crucial for clinical applications. Traditional manual cell counting using an optical bright-field microscope is time-consuming and needs an expert operator. In this study, the senescence cells were segmented and counted automatically by deep learning algorithms. However, well-performing deep learning algorithms require large numbers of labeled datasets. The manual labeling is time consuming and needs an expert. This makes deep learning-based automated counting process impractically expensive. To address this challenge, self-supervised learning based approach was implemented. The approach incorporates representation level contrastive learning component into the instance segmentation algorithm for efficient senescent cell segmentation with limited labeled data. Test results showed that the proposed model improves mean average precision and mean average recall of downstream segmentation task by 8.3% and 3.4% compared to original segmentation model.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Protocol for Cell Surface Biotinylation of Magnetic Labeled and Captured Human Peripheral Blood Mononuclear Cells
    (Elsevier, 2022) Ayaz Güner, Şerife; Acar, Mustafa Burak; Boyvat, Dudu; Güner, Hüseyin; Bozalan, Habibe; Güzel, Melis; Yıldır, Selin Kübra; Altınsoy, Nilay; Fındık, Fatma; Karakükçü, Musa; Özcan, Servet
    Analysis of the surfaceome of a blood cell subset requires cell sorting, followed by surface protein enrichment. Here, we present a protocol combining magnetically activated cell sorting (MACS) and surface biotinylation of the target cell subset from human peripheral blood mononuclear cells (PBMCs). We describe the steps for isolating target cells and their in-column surface biotinylation, followed by isolation and mass spectrometry analysis of biotinylated proteins. The protocol enables in-column surface biotinylation of specific cell subsets with minimal membrane disruption.