Browsing Makale Koleksiyonu by Author "Rifaioğlu, Ahmet Süreyya"
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The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
Zhou, Naihui; Jiang, Yuxiang; Bergquist, Timothy R.; Lee, Alexandra J.; Kacsoh, Balint Z.; Crocker, Alex W.; Friedberg, Iddo; Rifaioğlu, Ahmet Süreyya (Bmc, 2019)Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the ... -
DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks
Rifaioğlu, Ahmet Süreyya; Doğan, Tunca; Martin, Maria Jesus; Çetin-Atalay, Rengül; Atalay, Volkan (Nature Publishing Group, 2019)Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required. Recently, deep learning based methods have outperformed ... -
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations
Rifaioğlu, Ahmet Süreyya; Nalbat, Esra; Atalay, Volkan; Martin, Maria Jesus; Çetin-Atalay, Rengül; Doğan, Tunca (Royal Soc Chemistry, 2020)The identification of physical interactions between drug candidate compounds and target biomolecules is an important process in drug discovery. Since conventional screening procedures are expensive and time consuming, ... -
ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature
Dalkıran, Alperen; Rifaioğlu, Ahmet Süreyya; Martin, Maria Jesus; Çetin-Atalay, Rengül; Atalay, Volkan; Doğan, Tunca (BMC, 2018)Background: The automated prediction of the enzymatic functions of uncharacterized proteins is a crucial topic in bioinformatics. Although several methods and tools have been proposed to classify enzymes, most of these ... -
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 ... -
Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases
Rifaioğlu, Ahmet Süreyya; Ataş, Heval; Martin, Maria Jesus; Çetin-Atalay, Rengül; Atalay, Volkan; Doğan, Tunca (Oxford Univ Press, 2019)The identification of interactions between drugs/compounds and their targets is crucial for the development of new drugs. In vitro screening experiments (i.e. bioassays) are frequently used for this purpose; however, ...