Aybar Can Acar

E-mail

acacar@metu.edu.tr

Department

Graduate School of Informatics

ORCID

0000-0001-5694-8675

Scopus Author ID

8896015200

An integrative framework for clinical diagnosis and knowledge discovery from exome sequencing data Shojaei, Mona; Mohammadvand, Navid; DOĞAN, TUNCA; Alkan, Can; Çetin Atalay, Rengül; Acar, Aybar Can (2024-02-01) Non-silent single nucleotide genetic variants, like nonsense changes and insertion-deletion variants, that affect protein function and length substantially are prevalent and are frequently misclassified. The low sensitivit...
3D Simulation and Comparative Analysis of Immune System Cell Micro-Level Responses in Virtual Reality and Mixed Reality Environments Kaya, Hanifi Tuğşad; Sürer, Elif; Acar, Aybar Can (2023-10-18)
Transfer learning for drug–target interaction prediction Dalkıran, Alperen; Atakan, Ahmet; Rifaioğlu, Ahmet Süreyya; Martin, Maria J; Çetin Atalay, Rengül; Acar, Aybar Can; Doğan, Tunca; Atalay, Mehmet Volkan (2023-06-01) MotivationUtilizing AI-driven approaches for drug–target interaction (DTI) prediction require large volumes of training data which are not available for the majority of target proteins. In this study, we investigate the us...
Loss of the Nuclear Envelope Protein LAP1B Disrupts the Myogenic Differentiation of Patient-Derived Fibroblasts Kayman Kürekçi, Gülsüm; Acar, Aybar Can; Dinçer, Pervin R. (2022-11-01) Lamina-associated polypeptide 1 (LAP1) is a ubiquitously expressed inner nuclear membrane protein encoded by TOR1AIP1, and presents as two isoforms in humans, LAP1B and LAP1C. While loss of both isoforms results in a multi...
A Protein Representation Model for Low-Data Protein Function Prediction Unsal, Serbulent; Özdemir, Sinem; Özdinç, Işık; Bayraklı, Amine; Albayrak, Muammer; Turhan, Kemal; Dogan, Tunca; Acar, Aybar Can (Orta Doğu Teknik Üniversitesi Enformatik Enstitüsü; 2022-10)
Principal microbial groups: compositional alternative to phylogenetic grouping of microbiome data Boyraz, Asli; Pawlowsky-Glahn, Vera; Jose Egozcue, Juan; Acar, Aybar Can (2022-08-01) Statistical and machine learning techniques based on relative abundances have been used to predict health conditions and to identify microbial biomarkers. However, high dimensionality, sparsity and the compositional nature...
Learning functional properties of proteins with language models Unsal, Serbulent; Atas, Heval; ALBAYRAK, MUAMMER; TURHAN, KEMAL; Acar, Aybar Can; DOĞAN, TUNCA (2022-03-01) Data-centric approaches have been used to develop predictive methods for elucidating uncharacterized properties of proteins; however, studies indicate that these methods should be further improved to effectively solve crit...
Defining a master curve of abdominal aortic aneurysm growth and its potential utility of clinical management Akkoyun, Emrah; Gharahi, Hamidreza; Kwon, Sebastian T.; Zambrano, Byron A.; Rao, Akshay; Acar, Aybar Can; Lee, Whal; Baek, Seungik (2021-09-01) The maximum diameter measurement of an abdominal aortic aneurysm (AAA), which depends on orthogonal and axial cross-sections or maximally inscribed spheres within the AAA, plays a significant role in the clinical decision ...
Real-time Malaria Parasite Screening in Thick Blood Smears for Low-Resource Setting Chibuta, Samson; Acar, Aybar Can (Springer Science and Business Media LLC, 2020-06-01) Malaria is a serious public health problem in many parts of the world. Early diagnosis and prompt effective treatment are required to avoid anemia, organ failure, and malaria-associated deaths. Microscopic analysis of bloo...
Predicting abdominal aortic aneurysm growth using patient-oriented growth models with two-step Bayesian inference Akkoyun, Emrah; Kwon, Sebastian T.; Acar, Aybar Can; Lee, Whal; Baek, Seungik (Elsevier BV, 2020-02-01) Objective: For small abdominal aortic aneurysms (AAAs), a regular follow-up examination is recommended every 12 months for AAAs of 30-39 mm and every six months for AAAs of 40-55 mm. Follow-up diameters can determine if a ...

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