Recent Submissions

  • Rule based segmentation of colon glands 

    Yücel, Simge (Bilkent University, 2018-09)
    Colon adenocarcinoma, which accounts for more than 90 percent of all colorectal cancers, originates from epithelial cells that form colon glands. Thus, for its diagnosis and grading, it is important to examine the ...
  • Recognition of occupational therapy exercises for cerebral palsy 

    Ongun, Mehmet Faruk (Bilkent University, 2018-09)
    Depth camera-based virtual rehabilitation systems are gaining traction in occupational therapy for approaching patients with cerebral palsy. When developing such a system, a domain speci c exercise recognition method is ...
  • Fog supported wireless sensor networks for forest fire detection 

    Amira, Fouad (Bilkent University, 2018-09)
    Fog computing is a new paradigm that aims to extend the concept of cloud computing to the edge of the network, providing the end users network with extra storage and processing power. One big contribution of Fog computing ...
  • Characterization of large structural variation using linked-reads 

    Karaoğlanoğlu, Fatih (Bilkent University, 2018-09)
    Many algorithms aimed at characterizing genomic structural variation (SV) have been developed since the inception of high-throughput sequencing. However, the full spectrum of SVs in the human genome is not yet assessed. ...
  • A producer-centric caching strategy for named data networking 

    Açacak, Hüseyin (Bilkent University, 2018-09)
    With growing number of users and content on Internet, the existing Internet architecture needs to evolve to be more efficient to find and carry content, and Named Data Networking (NDN) is a new Internet architecture ...
  • Privacy protection for spatial trajectories against brute-force attacks 

    Arslan, Dorukhan (Bilkent University, 2018-08)
    The prevalence of Global Positioning System (GPS) equipped mobile devices and wireless communication technologies have resulted in widespread development of location-based services (LBS). As some typical examples of LBS, ...
  • Quantifying and protecting genomic privacy 

    Mobayenjarihani, Mohammad (Bilkent University, 2018-08)
    Today, genome sequencing is more accessible and affordable than ever. It is also possible for individuals to share their genomic data with service providers or on public websites. Although genomic data has significant ...
  • Deep learning based cell segmentation in histopathological images 

    Doğan, Deniz (Bilkent University, 2018-08)
    In digital pathology, cell imaging systems allow us to comprehend histopathological events at the cellular level. The first step in these systems is generally cell segmentation, which substantially affects the subsequent ...
  • Deepkinzero: zero-shot learning for predicting kinase phosphorylation sites 

    Deznabi, Iman (Bilkent University, 2018-08)
    Protein kinases are a large family of enzymes that catalyze the phosphorylation of other proteins. By acting as molecular switches for protein activity, the phosphorylation events regulate intracellular signal transduction, ...
  • Parallel streaming graph partitioning utilizing multilevel framework 

    Jafari, Nazanin (Bilkent University, 2018-08)
    Graph partitioning is widely used for e cient parallelization of a variety of applications. Streaming graph partitioning is a one pass partitioning solution provided to overcome high computation costs of o ine graph ...
  • Spatio-temporal gene discovery for autism spectrum disorder 

    Korman, Utku (Bilkent University, 2018-08)
    Whole Exome Sequencing (WES) studies for Autism Spectrum Disorder (ASD) could identify only around six dozen risk genes to date, because the genetic architecture of the disorder is highly complex. To speed the gene ...
  • Privacy-preserving computation and robust watermarking techniques for healthcare data 

    Sav, Sinem (Bilkent University, 2018-08)
    Health and genomic data is sensitive in terms of carrying private information about individuals. One can infer inherited/genetic disorders, their occurrence probabilities, information about race, and kinship by analyzing ...
  • Spadis: selecting predictive and diverse SNPS in GWAS 

    Yılmaz, Serhan (Bilkent University, 2018-08)
    Phenotypic heritability of complex traits and diseases is seldom explained by individual genetic variants identi ed in genome-wide association studies (GWAS). Many methods have been developed to select a subset of variant ...
  • Improvements on pathwaymapper: a collaborative pathway curation tool 

    Dervishi, Leonard (Bilkent University, 2018-07)
    Information visualization focuses on visually representing abstract data to amplify human cognition. Graph visualization is one of the most common types in the eld of information visualization because of its capabilities ...
  • Methods and tools for synchronized visualization of evolving networks 

    Safarli, Ilkin (Bilkent University, 2018-07)
    Graph visualization is a powerful tool to convey and analyze relational information in the form of networks such as biological networks, social networks, and computer networks. Abundant research has been conducted on the ...
  • Fine-grained object recognition in remote sensing imagery 

    Sümbül, Gencer (Bilkent University, 2018-06)
    Fine-grained object recognition aims to determine the type of an object in domains with a large number of sub-categories. The steadily increase in spatial and spectral resolution entailing new details in remote sensing ...
  • High throughput udp-based peer-to-peer secure data transfer 

    Doğan, Fadime Tuğba (Bilkent University, 2018-06)
    High throughput sequencing (HTS) platforms have been developed in recent years. These technologies enable researchers to answer a wide range of biological questions by obtaining whole or targeted segments of genomes of ...
  • Image super-resolution using deep feedforward neural networks in spectral domain 

    Aydın, Onur (Bilkent University, 2018-03)
    With recent advances in deep learning area, learning machinery and mainstream approaches in computer vision research have changed dramatically from hardcoded features combined with classi ers to end-to-end trained deep ...
  • Analysis of parallel iterative graph applications on shared memory systems 

    Atik, Funda (Bilkent University, 2018-01)
    Graph analytics have come to prominence due to their wide applicability to many phenomena of real world such as social networks, protein-protein interactions, power grids, transportation networks, and other domains. Despite ...
  • Energy efficient dynamic virtual machine allocation with cpu usage prediction in cloud datacenters 

    Urul, Gökalp (Bilkent University, 2018-01)
    With tremendous increase in Internet capacity and services, the demand for cloud computing has also grown enormously. This enormous demand for cloud based data storage and processing forces cloud providers to optimize ...

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