Aybar Can Acar

E-mail

acacar@metu.edu.tr

Department

Graduate School of Informatics

ORCID

0000-0001-5694-8675

Scopus Author ID

8896015200

Molecular contrastive learning with graph attention network (MoCL-GAT) for enhanced molecular representation Dalkıran, Alperen; Rifaioğlu, Ahmet Süreyya; Atalay, Rengül; Acar, Aybar Can; DOĞAN, TUNCA; Atalay, Mehmet Volkan (2026-12-01) Background: Learning the representation of molecules is crucial for drug discovery but is often hindered by the scarcity of labeled experimental data, which limits the performance of supervised machine learning models. Whi...
DTA-GNN: a toolkit for constructing target-specific drug–target affinity datasets and training graph neural networks Özsari, Gökhan; Rifaioğlu, Ahmet Süreyya; Acar, Aybar Can; DOĞAN, TUNCA; Atalay, Mehmet Volkan (2026-06-01) Drug–target affinity (DTA) prediction is a key task in computational drug discovery, yet current research is often compromised by data leakage and non-reproducible preprocessing. We present DTA-GNN, an end-to-end Python to...
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 ...

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