A. Rifaioglu

发表

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Jari Björne, Tapio Salakoski, Giorgio Valentini, 2019, Genome Biology.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage

David C. Jones, S. Pfister, J. Saez-Rodriguez, 2022, bioRxiv.

DEEPScreen: high performance drug–target interaction prediction with convolutional neural networks using 2-D structural compound representations

Volkan Atalay, Tunca Doğan, María Martín, 2018, bioRxiv.

ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature

R. Cetin-Atalay, V. Atalay, M. Martin, 2018, BMC Bioinform..

Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools

R. Cetin-Atalay, D. Kahraman, A. Rifaioglu, 2021, Journal of Gastrointestinal Cancer.

Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases

Volkan Atalay, Heval Atas, Rengul Cetin-Atalay, 2018, Briefings Bioinform..

CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations

R. Cetin-Atalay, V. Atalay, M. Martin, 2021, Nucleic acids research.

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Tapio Salakoski, Feng Zhang, Paolo Fontana, 2019, Genome Biology.

ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature

Maria Jesus Martin, Rengül Çetin-Atalay, Volkan Atalay, 2018, BMC Bioinformatics.

Large‐scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants

Rabie Saidi, Tunca Doğan, Tulin Ersahin, 2018, Proteins.

Multi-task Deep Neural Networks in Automated Protein Function Prediction

Rengul Cetin-Atalay, Ahmet Sureyya Rifaioglu, Maria Jesus Martin, 2017, 1705.04802.

iBioProVis: interactive visualization and analysis of compound bioactivity space

Rengül Çetin-Atalay, Volkan Atalay, Aybar C. Acar, 2020, Bioinform..

MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery

A S Rifaioglu, R Cetin Atalay, D Cansen Kahraman, 2020, Bioinform..

ProFAB - open protein functional annotation benchmark

A. Rifaioglu, A. Acar, Tunca Dogan, 2023, Briefings Bioinform..

Predicting the Specificity- Determining Positions of Receptor Tyrosine Kinase Axl

J. Rodrigues, E. Karaca, A. Rifaioglu, 2021, Frontiers in Molecular Biosciences.

CROssBAR: Comprehensive Resource of Biomedical Relations with Deep Learning Applications and Knowledge Graph Representations

Volkan Atalay, Rabie Saidi, Heval Atas, 2020, bioRxiv.

Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks

A. Olğaç, D. Kahraman, A. Rifaioglu, 2023, ArXiv.

Transfer learning for drug–target interaction prediction

V. Atalay, A. Rifaioglu, A. Acar, 2023, Bioinformatics.

Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases

R. Cetin-Atalay, V. Atalay, M. Martin, 2018, Briefings Bioinform..

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage

Maxwell P. Gold, K. Rippe, K. Pajtler, 2024, Nature communications.