Tunca Doğan

17.1k total citations · 1 hit paper
28 papers, 1.2k citations indexed

About

Tunca Doğan is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Tunca Doğan has authored 28 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 16 papers in Computational Theory and Mathematics and 5 papers in Materials Chemistry. Recurrent topics in Tunca Doğan's work include Computational Drug Discovery Methods (16 papers), Machine Learning in Bioinformatics (15 papers) and Protein Structure and Dynamics (10 papers). Tunca Doğan is often cited by papers focused on Computational Drug Discovery Methods (16 papers), Machine Learning in Bioinformatics (15 papers) and Protein Structure and Dynamics (10 papers). Tunca Doğan collaborates with scholars based in Türkiye, United Kingdom and United States. Tunca Doğan's 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 Alex Bateman and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Tunca Doğan

26 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

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

2018 363 citations Ahmet Süreyya Rifaioğlu, Heval Ataş et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tunca Doğan Türkiye	13	859	615	220	65	59	28	1.2k
Ahmet Süreyya Rifaioğlu Türkiye	8	672 0.8×	529 0.9×	174 0.8×	55 0.8×	39 0.7×	15	896
Michael Hsing Canada	19	950 1.1×	600 1.0×	178 0.8×	71 1.1×	48 0.8×	35	1.6k
Eloy Félix United Kingdom	6	545 0.6×	625 1.0×	230 1.0×	88 1.4×	59 1.0×	11	1.0k
Anh‐Tien Ton Canada	12	614 0.7×	802 1.3×	210 1.0×	69 1.1×	40 0.7×	13	1.2k
Wen Torng United States	7	632 0.7×	715 1.2×	337 1.5×	74 1.1×	65 1.1×	7	1.0k
Miha Škalič Spain	9	1.1k 1.2×	844 1.4×	445 2.0×	98 1.5×	42 0.7×	11	1.4k
Nils Weskamp Germany	14	603 0.7×	587 1.0×	216 1.0×	96 1.5×	70 1.2×	21	905
Fangping Wan United States	13	847 1.0×	523 0.9×	162 0.7×	49 0.8×	87 1.5×	18	1.1k
Elif Özkırımlı Türkiye	5	988 1.2×	1.0k 1.6×	393 1.8×	97 1.5×	55 0.9×	5	1.2k
Ana C. Puhl United States	16	494 0.6×	378 0.6×	165 0.8×	88 1.4×	43 0.7×	48	1.0k

Countries citing papers authored by Tunca Doğan

Since Specialization

Citations

This map shows the geographic impact of Tunca Doğan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tunca Doğan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tunca Doğan more than expected).

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-authorship network of co-authors of Tunca Doğan

This figure shows the co-authorship network connecting the top 25 collaborators of Tunca Doğan. A scholar is included among the top collaborators of Tunca Doğan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tunca Doğan. Tunca Doğan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Yining, Xin Wang, Tunca Doğan, et al.. (2025). Mpox: disease manifestations and therapeutic development. Journal of Virology. 99(9). e0015225–e0015225. 1 indexed citations

Kahraman, Deniz, et al.. (2025). Target-specific de novo design of drug candidate molecules with graph-transformer-based generative adversarial networks. Nature Machine Intelligence. 7(9). 1524–1540.

Doğan, Tunca, et al.. (2024). Mutual annotation‐based prediction of protein domain functions with Domain2GO. Protein Science. 33(6). e4988–e4988. 3 indexed citations

Rifaioğlu, Ahmet Süreyya, María Martin, Rengül Çetin-Atalay, et al.. (2023). Transfer learning for drug–target interaction prediction. Bioinformatics. 39(Supplement_1). i103–i110. 35 indexed citations

Doğan, Tunca, et al.. (2023). SELFormer: molecular representation learning via SELFIES language models. Machine Learning Science and Technology. 4(2). 25035–25035. 35 indexed citations

Ataş, Heval & Tunca Doğan. (2023). How to approach machine learning-based prediction of drug/compound–target interactions. Journal of Cheminformatics. 15(1). 16–16. 23 indexed citations

Ataş, Heval, et al.. (2022). Learning functional properties of proteins with language models. Nature Machine Intelligence. 4(3). 227–245. 106 indexed citations

Doğan, Tunca, et al.. (2022). Machine learning-based prediction of drug approvals using molecular, physicochemical, clinical trial, and patent-related features. Expert Opinion on Drug Discovery. 17(12). 1425–1441. 5 indexed citations

Doğan, Tunca, Heval Ataş, Vishal Joshi, et al.. (2021). CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations. Nucleic Acids Research. 49(16). e96–e96. 26 indexed citations

10.

Çetin-Atalay, Rengül, Deniz Kahraman, Ahmet Süreyya Rifaioğlu, et al.. (2021). Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools. Journal of Gastrointestinal Cancer. 52(4). 1266–1276. 2 indexed citations

11.

Doğan, Tunca, Marcus Baumann, Heval Ataş, et al.. (2021). Protein domain-based prediction of drug/compound–target interactions and experimental validation on LIM kinases. PLoS Computational Biology. 17(11). e1009171–e1009171. 14 indexed citations

12.

Ataş, Heval, et al.. (2020). Learning Functional Properties of Proteins with Language Models. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

13.

Rifaioğlu, Ahmet Süreyya, Rengül Çetin-Atalay, Deniz Kahraman, et al.. (2020). MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery. Bioinformatics. 37(5). 693–704. 77 indexed citations

14.

Rifaioğlu, Ahmet Süreyya, Tunca Doğan, María Martin, Rengül Çetin-Atalay, & Volkan Atalay. (2019). DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks. Scientific Reports. 9(1). 7344–7344. 101 indexed citations

15.

Doğan, Tunca. (2018). HPO2GO: prediction of human phenotype ontology term associations for proteins using cross ontology annotation co-occurrences. PeerJ. 6. e5298–e5298. 25 indexed citations

16.

Doğan, Tunca, et al.. (2018). A Structural Perspective on the Modulation of Protein-Protein Interactions with Small Molecules. Current Topics in Medicinal Chemistry. 18(8). 700–713. 4 indexed citations

17.

Ataş, Heval, Nurcan Tunçbağ, & Tunca Doğan. (2018). Phylogenetic and Other Conservation-Based Approaches to Predict Protein Functional Sites. Methods in molecular biology. 1762. 51–69. 5 indexed citations

18.

Rifaioğlu, Ahmet Süreyya, et al.. (2018). ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature. BMC Bioinformatics. 19(1). 334–334. 111 indexed citations

19.

Doğan, Tunca, Alistair MacDougall, Rabie Saidi, et al.. (2016). UniProt-DAAC: domain architecture alignment and classification, a new method for automatic functional annotation in UniProtKB. Bioinformatics. 32(15). 2264–2271. 30 indexed citations

20.

Doğan, Tunca & Bilge Karaçalı. (2013). Automatic Identification of Highly Conserved Family Regions and Relationships in Genome Wide Datasets Including Remote Protein Sequences. PLoS ONE. 8(9). e75458–e75458. 8 indexed citations

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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