Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik

Permanent URI for this collectionhttps://hdl.handle.net/11147/9

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Now showing 1 - 10 of 22
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 4
    Deep Learning Based Segmentation Pipeline for Label-Free Phase-Contrast Microscopy Images
    (IEEE, 2020) Ayanzadeh, Aydın; Yalçın Özuysal, Özden; Okvur, Devrim Pesen; Önal, Sevgi; Töreyin, Behçet Uğur; Ünay, Devrim
    The segmentation of cells is necessary for biologists in the morphological statistics for quantitative and qualitative analysis in Phase-contrast Microscopy (PCM) images. In this paper, we address the cell segmentation problem in PCM images. Deep Neural Networks (DNNs) commonly is initialized with weights from a network pre-trained on a large annotated data set like ImageNet have superior performance than those trained from scratch on a small dataset. Here, we demonstrate how encoder-decoder type architectures such as U-Net and Feature Pyramid Network (FPN) can be improved by an alternative encoder which pre-trained on the ImageNet dataset. In particular, our experimental results confirm that the image descriptors from ResNet-18 are highly effective in accurate prediction of the cell boundary and have higher Intersection over Union (IoU) in comparison to the classical U-Net and require fewer training epochs.
  • Conference Object
    Citation - Scopus: 2
    Yara İyileşmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-çalışma
    (IEEE, 2020) Mayalı, Berkay; Şaylığ, Orkun; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Töreyin, Behçet Uğur; Ünay, Devrim
    Collective cell analysis from microscopy image series is important for wound healing research. Computer-based automation of such analyses may help in rapid acquisition of reliable and reproducible results. In this study phase -contrast optical microscopy image series of an in-vitro wound healing essay is manually delineated by two experts and its analysis is realized, traditional image processing and deep learning based approaches for automated segmentation of wound area are developed and their perlOrmance comparisons are carried out.
  • Conference Object
    Assessment of Cell Cycle and Viability of Magnetic Levitation Assembled Cellular Structures
    (IEEE, 2020) Anıl İnevi, Müge; Ünal, Yağmur Ceren; Yaman, Sena; Tekin, H. Cumhur; Meşe, Gülistan; Meşe, Gülistan
    Label-free magnetic levitation is one of the most recent Earth-based in vitro techniques that simulate the microgravity. This technique offers a great opportunity to biofabricate scaffold-free 3-dimensional (3D) structures and to study the effects of microgravity on these structures. In this study, self-assembled 3D living structures were fabricated in a paramagnetic medium by magnetic levitation technique and effects of the technique on cellular health was assessed. This magnetic force-assisted assembly system applied here offers broad applications in several fields, such as space biotechnology and bottom-up tissue engineering.
  • Conference Object
    Pros and Cons of Plant Nuclear Protein Enrichment
    (Mendel University of Agriculture and Forestry Brno, 2016) Svetlakova, Anna; Cerna, Hana; Novak, Jan; Şelale, Hatice
    Nuclear proteome contains important regulatory proteins. To improve the detection of these proteins, Percoll gradient-based fractionation techniques have been developed and optimized. However, owing to the ever increasing sensitivity of identification methods based on liquid chromatography and mass spectrometry, the time and material consuming fractionation methods may no longer be necessary. Here, we show that a Percoll-based nuclear protein fractionation of tomato leaf proteome increased the number of detected proteins, but at least some nuclear proteins were lost or depleted in the process.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 8
    Distinguishing Between Microrna Targets From Diverse Species Using Sequence Motifs and K-Mers
    (SCITEPRESS, 2017) Yousef, Malik; Khalifa, Waleed; Acar, İlhan Erkin; Allmer, Jens
    A disease phenotype is often due to dysregulation of gene expression. Post-translational regulation of protein abundance by microRNAs (miRNAs) is, therefore, of high importance in, for example, cancer studies. MicroRNAs provide a complementary sequence to their target messenger RNA (mRNA) as part of a complex molecular machinery. Known miRNAs and targets are listed in miRTarBase for a variety of organisms. The experimental detection of such pairs is convoluted and, therefore, their computational detection is desired which is complicated by missing negative data. For machine learning, many features for parameterization of the miRNA targets are available and k-mers and sequence motifs have previously been used. Unrelated organisms like intracellular pathogens and their hosts may communicate via miRNAs and, therefore, we investigated whether miRNA targets from one species can be differentiated from miRNA targets of another. To achieve this end, we employed target information of one species as positive and the other as negative training and testing data. Models of species with higher evolutionary distance generally achieved better results of up to 97% average accuracy (mouse versus Caenorhabditis elegans) while more closely related species did not lead to successful models (human versus mouse; 60%). In the future, when more targeting data becomes available, models can be established which will be able to more precisely determine miRNA targets in hostpathogen systems using this approach.
  • Conference Object
    Citation - WoS: 7
    Citation - Scopus: 11
    Cell Segmentation of 2d Phase-Contrast Microscopy Images With Deep Learning Method
    (Institute of Electrical and Electronics Engineers Inc., 2019) Ayanzadeh, Aydın; Yağar, Hüseyin Onur; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Töreyin, Behçet Uğur; Unay, Devrim; Önal, Sevgi
    The quantitative and qualitative ascertainment of cell culture is integral to the robust determination of the cell structure analysis. Microscopy cell analysis and the epithet structures of cells in cell cultures are momentous in the fields of the biological research process. In this paper, we addressed the problem of phase-contrast microscopy under cell segmentation application. In our proposed method, we utilized the state-of-the-art deep learning models trained on our proposed dataset. Due to the low number of annotated images, we propose a multi-resolution network which is based on the U-Net architecture. Moreover, we applied multi-combination augmentation to our dataset which has increased the performance of segmentation accuracy significantly. Experimental results suggest that the proposed model provides superior performance in comparison to traditional state-of-the-art segmentation algorithms.
  • Book Part
    Citation - WoS: 10
    Synteny Among Solanaceae Genomes
    (Springer, 2016) Frary, Amy; Doğanlar, Sami; Frary, Anne
    The Solanaceae was among the first plant families to be analyzed via comparative mapping and thus was a pioneer in the realm of synteny studies. Analyses of chromosome content and organization have employed a range of techniques, including linkage mapping of genes and molecular markers, physical mapping via fluorescence in situ hybridization, and sequencing of relatively small genomic segments as well as the complete sequencing of the tomato genome. Early comparisons in the family involved tomato and its close relative potato and have extended outward to include eggplant, pepper, tobacco, and petunia. Not surprisingly, the degree of synteny among these species is a function of the time since their divergence, with inversion, translocation, and transposition being the chief mechanisms of chromosome rearrangement. The results of this work provide important insight into the modes and tempo of plant genome evolution while serving a practical purpose as well: knowledge of genome synteny and colinearity makes it easier to leverage resources from one species to another in this agronomically important family.
  • Book Part
    Citation - WoS: 59
    Citation - Scopus: 68
    Stem Cell Therapy for Multiple Sclerosis
    (Springer, 2019) Genç, Bilgesu; Bozan, Hemdem Rodi; Genç, Şermin; Genç, Kürşad
    Multiple sclerosis (MS) is a chronic inflammatory, autoimmune, and neurodegenerative disease of the central nervous system (CNS). It is characterized by demyelination and neuronal loss that is induced by attack of autoreactive T cells to the myelin sheath and endogenous remyelination failure, eventually leading to functional neurological disability. Although recent evidence suggests that MS relapses are induced by environmental and exogenous triggers such as viral infections in a genetic background, its very complex pathogenesis is not completely understood. Therefore, the efficiency of current immunosuppression-based therapies of MS is too low, and emerging disease-modifying immunomodulatory agents such as fingolimod and dimethyl fumarate cannot stop progressive neurodegenerative process. Thus, the cell replacement therapy approach that aims to overcome neuronal cell loss and remyelination failure and to increase endogenous myelin repair capacity is considered as an alternative treatment option. A wide variety of preclinical studies, using experimental autoimmune encephalomyelitis model of MS, have recently shown that grafted cells with different origins including mesenchymal stem cells (MSCs), neural precursor and stem cells, and induced-pluripotent stem cells have the ability to repair CNS lesions and to recover functional neurological deficits. The results of ongoing autologous hematopoietic stem cell therapy studies, with the advantage of peripheral administration to the patients, have suggested that cell replacement therapy is also a feasible option for immunomodulatory treatment of MS. In this chapter, we overview cell sources and applications of the stem cell therapy for treatment of MS. We also discuss challenges including those associated with administration route, immune responses to grafted cells, integration of these cells to existing neural circuits, and risk of tumor growth. Finally, future prospects of stem cell therapy for MS are addressed.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 6
    Faz Kontrast Optik Mikroskopi Zaman Serisi Görüntülerinde Hücrelerin Otomatik Bölütlenmesi
    (Institute of Electrical and Electronics Engineers Inc., 2019) Binici, Rıfkı Can; Şahin, Umut; Ayanzadeh, Aydın; Töreyin, Behçet Uğur; Önal, Sevgi; Okvur, Devrim Pesen; Yalçın Özuysal, Özden; Ünay, Devrim
    Faz kontrast optik mikroskopi hücrelerin canlı ortamlarında zamana bağlı incelenmesi için tercih edilen görüntüleme yöntemidir. Bu yöntem ile elde edilen zaman serisi görüntülerinde hücrelerin bölütlenmesi işi hücre biyolojisi araştırmacılarının çözümüne ihtiyaç duyduğu emek yoğun ve zaman alan bir iştir. Bu çalışmada faz kontrast optik mikroskopi zaman serilerinde hücrelerin otomatik bölütlenmesi için geleneksel görüntü işleme ve derin öğrenme temelli yöntemler önerilmiş ve başarımları elle işaretlenmiş veri kümelerinde nicel olarak ölçülmüştür.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 4
    Biofabrication of Cellular Structures Using Weightlessness as a Biotechnological Tool
    (IEEE, 2019) Anıl İnevi, Müge; Sarıgil, Öykü; Yaman, Sena; Yalçın Özuysal, Özden; Meşe, Gülistan; Tekin, Hüseyin Cumhur; Özçivici, Engin
    Gravity is an important biomechanical signal effecting the morphology and function of organisms. Reduction of gravitational forces, as experienced during spaceflight, cause alterations in the biological systems. Magnetic levitation technique is one of the most recent ground-based technology to mimic weightlessness environment. In addition to providing a platform to investigate biological effects of the weightlessness, this platform presents a novel opportunity to biofabricate 3-dimensional (3D) structures in a scaffold-and nozzle-free fashion. In this study, various controllable self-assembled 3D living structures were fabricated via magnetic levitation technique. This strategy may offer an easy and cost-effective opportunity for a wide range of space biotechnology researches.