Yazar "Atalay, Rengül Çetin" için listeleme
-
CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations
Doğan, Tunca; Ataş, Heval; Joshi, Vishal; Atakan, Ahmet; Rifaioğlu, Ahmet Süreyya; Nalbat, Esra; Nightingale, Andrew; Saidi, Rabie; Volynkin, Vladimir; Zellner, Hermann; Atalay, Rengül Çetin; Martin, Maria; Atalay, Volkan (Oxford Academic, 2021)Systemic analysis of available large-scale biological/biomedical data is critical for studying biological mechanisms, and developing novel and effective treatment approaches against diseases. However, different layers of ... -
iBioProVis: interactive visualization and analysis of compound bioactivity space
Dönmez, Ataberk; Rifaioğlu, Ahmet Süreyya; Acar, Aybar; Doğan, Tunca; Atalay, Rengül Çetin; Atalay, Volkan (NLM (Medline), 2020)iBioProVis is an interactive tool for visual analysis of the compound bioactivity space in the context of target proteins, drugs and drug candidate compounds. iBioProVis tool takes target protein identifiers and, optionally, ... -
Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants
Rifaioğlu, Ahmet Süreyya; Doğan, Tunca; Saraç, Ömer Sinan; Erşahin, Tülin; Saidi, Rabie; Atalay, Mehmet Volkan; Martin, Maria Jesus; Atalay, Rengül Çetin (Wiley, 2018)Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and ... -
SLPred: a multi-view subcellular localization prediction tool for multi-location human proteins
Özsarı, Gökhan; Rifaioğlu, Ahmet Süreyya; Atakan, Ahmet; Tunca, Doğan; Martin, Maria Jesus; Atalay, Rengül Çetin; Atalay, Volkan (Oxford University Press, 2022)Accurate prediction of the subcellular locations (SLs) of proteins is a critical topic in protein science. In this study, we present SLPred, an ensemble-based multi-view and multi-label protein subcellular localization ... -
Transfer learning for drug–target interaction prediction
Dalkıran, Alperen; Atakan, Ahmet; Rifaioğlu, Ahmet Süreyya; Martin, Maria Jesús; Atalay, Rengül Çetin; Acar, Aybar Can; Doǧan, Tunca; Atalay, Volkan (Oxford University Press, 2023)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 ...
