Tunca Doğan

17.1k citations

28 papers · 1.2k · 1 hit paper · h-index 13

Impact in

Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Molecular Biology top 10%
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Genetics, Bioinformatics, and Biomedical Research

Papers in

Molecular Biology 25
- Machine Learning in Bioinformatics 15
- Protein Structure and Dynamics 10
- Bioinformatics and Genomic Networks 8
- Genomics and Phylogenetic Studies 7
- Biomedical Text Mining and Ontologies 3
- RNA and protein synthesis mechanisms 3
Computational Theory and Mathematics 16
- Computational Drug Discovery Methods 16

Co-authors: María Martin (11 shared papers)Rengül Çetin-Atalay (13 shared papers)Volkan Atalay (12 shared papers)Ahmet Süreyya Rifaioğlu (13 shared papers)Heval Ataş (8 shared papers)Aybar C. Acar (6 shared papers)Kemal Turhan (2 shared papers)Deniz Kahraman (4 shared papers)
Journals: Bioinformatics (5 papers)Nature Machine Intelligence (2 papers)Briefings in Bioinformatics (2 papers)Current Topics in Medicinal Chemistry (1 paper)Scientific Reports (1 paper)
Partner nations: Türkiye United Kingdom United States

In The Last Decade

Tunca Doğan

26 papers receiving 1.1k citations

Tunca Doğan's Hit Papers

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Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases 2018 · 363 citations

Peers

Countries citing papers authored by Tunca Doğan

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Citations

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Fields of papers citing papers by Tunca Doğan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tunca Doğan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tunca Doğan. The network helps show where Tunca Doğan may publish in the future.

Co-authors

The 25 scholars most cited alongside Tunca Doğan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tunca Doğan Line = papers co-authored together Tunca Doğan links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases Briefings in Bioinformatics ·Ahmet Süreyya Rifaioğlu, Heval Ataş, María Martin, Rengül Çetin-Atalay, Volkan Atalay, Tunca Doğan Hit paper breakdown →	2018	363
2	DEEPScreen: high performance drug–target interaction prediction with convolutional neural networks using 2-D structural compound representations Chemical Science ·Ahmet Süreyya Rifaioğlu, Esra Nalbat, Volkan Atalay, María Martin, Rengül Çetin-Atalay, Tunca Doğan	2020	154
3	ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature BMC Bioinformatics ·Alperen Dalkıran, Ahmet Süreyya Rifaioğlu, María Martin, Rengül Çetin-Atalay, Volkan Atalay, Tunca Doğan	2018	111
4	Learning functional properties of proteins with language models Nature Machine Intelligence ·Serbülent Ünsal, Heval Ataş, Muammer Albayrak, Kemal Turhan, Aybar C. Acar, Tunca Doğan	2022	106
5	DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks Scientific Reports ·Ahmet Süreyya Rifaioğlu, Tunca Doğan, María Martin, Rengül Çetin-Atalay, Volkan Atalay	2019	101
6	MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery Bioinformatics ·Ahmet Süreyya Rifaioğlu, Rengül Çetin-Atalay, Deniz Kahraman, Tunca Doğan, María Martin, Volkan Atalay	2020	77
7	Transfer learning for drug–target interaction prediction Bioinformatics ·Alperen Dalkıran, Ahmet Atakan, Ahmet Süreyya Rifaioğlu, María Martin, Rengül Çetin-Atalay, Aybar C. Acar, Tunca Doğan, Volkan Atalay	2023	35
8	SELFormer: molecular representation learning via SELFIES language models Machine Learning Science and Technology ·Atakan Yüksel, Erva Ulusoy, Atabey Ünlü, Tunca Doğan	2023	35
9	UniProt-DAAC: domain architecture alignment and classification, a new method for automatic functional annotation in UniProtKB Bioinformatics ·Tunca Doğan, Alistair MacDougall, Rabie Saidi, Diego Poggioli, Alex Bateman, Claire O’Donovan, María Martin	2016	30
10	CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations Nucleic Acids Research ·Tunca Doğan, Heval Ataş, Vishal Joshi, Ahmet Atakan, Ahmet Süreyya Rifaioğlu, Esra Nalbat, Andrew Nightingale, Rabie Saidi, Vladimir Volynkin, Hermann Zellner, Rengül Çetin-Atalay, María Martin, Volkan Atalay	2021	26
11	HPO2GO: prediction of human phenotype ontology term associations for proteins using cross ontology annotation co-occurrences PeerJ ·Tunca Doğan	2018	25
12	How to approach machine learning-based prediction of drug/compound–target interactions Journal of Cheminformatics ·Heval Ataş, Tunca Doğan	2023	23
13	Protein domain-based prediction of drug/compound–target interactions and experimental validation on LIM kinases PLoS Computational Biology ·Tunca Doğan, Ece Akhan Güzelcan, Marcus Baumann, Altay Koyaş, Heval Ataş, Ian R. Baxendale, María Martin, Rengül Çetin-Atalay	2021	14
14	Large‐scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants Proteins Structure Function and Bioinformatics ·Ahmet Süreyya Rifaioğlu, Tunca Doğan, Ömer Saraç, Tülin Erşahin, Rabie Saidi, Volkan Atalay, María Martin, Rengül Çetin-Atalay	2017	10
15	Automatic Identification of Highly Conserved Family Regions and Relationships in Genome Wide Datasets Including Remote Protein Sequences PLoS ONE ·Tunca Doğan, Bilge Karaçalı	2013	8
16	iBioProVis: interactive visualization and analysis of compound bioactivity space Bioinformatics ·Ataberk Donmez, Ahmet Süreyya Rifaioğlu, Aybar C. Acar, Tunca Doğan, Rengül Çetin-Atalay, Volkan Atalay	2020	6
17	Phylogenetic and Other Conservation-Based Approaches to Predict Protein Functional Sites Methods in molecular biology ·Heval Ataş, Nurcan Tunçbağ, Tunca Doğan	2018	5
18	Machine learning-based prediction of drug approvals using molecular, physicochemical, clinical trial, and patent-related features Expert Opinion on Drug Discovery ·Fulya Ciray, Tunca Doğan	2022	5
19	Protein language models for predicting drug–target interactions: Novel approaches, emerging methods, and future directions Current Opinion in Structural Biology ·Atabey Ünlü, Erva Ulusoy, Melih Gökay Yiğit, Melih Darcan, Tunca Doğan	2025	5
20	A Structural Perspective on the Modulation of Protein-Protein Interactions with Small Molecules Current Topics in Medicinal Chemistry ·Habibe Cansu Demirel, Tunca Doğan, Nurcan Tunçbağ	2018	4

About Tunca Doğan

Tunca Doğan is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Immunology and Organic Chemistry, having authored 28 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (16 papers), Machine Learning in Bioinformatics (15 papers), Protein Structure and Dynamics (10 papers), Bioinformatics and Genomic Networks (8 papers), Genomics and Phylogenetic Studies (7 papers), Machine Learning in Materials Science (5 papers), Biomedical Text Mining and Ontologies (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Computational Theory and Mathematics (615 citations), Molecular Biology (859 citations), Health Informatics (12 citations), Biophysics (36 citations) and Materials Chemistry (220 citations). Tunca Doğan has collaborated with scholars based in Türkiye, United Kingdom and United States. Frequent co-authors include María Martin, Rengül Çetin-Atalay, Volkan Atalay, Ahmet Süreyya Rifaioğlu, Heval Ataş, Aybar C. Acar, Kemal Turhan, Deniz Kahraman, Rabie Saidi and Claire O’Donovan. Their work appears in journals such as Bioinformatics, Nature Machine Intelligence, Briefings in Bioinformatics, Current Topics in Medicinal Chemistry and Scientific Reports.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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