Yulia Dodonova

14 total papers · 485 total citations
5 papers, 277 citations indexed

About

Yulia Dodonova is a scholar working on Cognitive Neuroscience, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yulia Dodonova has authored 5 papers receiving a total of 277 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Cognitive Neuroscience, 2 papers in Molecular Biology and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Yulia Dodonova's work include Functional Brain Connectivity Studies (3 papers), Brain Tumor Detection and Classification (1 paper) and Neural dynamics and brain function (1 paper). Yulia Dodonova is often cited by papers focused on Functional Brain Connectivity Studies (3 papers), Brain Tumor Detection and Classification (1 paper) and Neural dynamics and brain function (1 paper). Yulia Dodonova collaborates with scholars based in Russia. Yulia Dodonova's co-authors include Mikhail Belyaev, Sergey Korolev, Leonid Zhukov, Anvar Kurmukov and Anna Tkachev and has published in prestigious journals such as .

In The Last Decade

Yulia Dodonova

5 papers receiving 273 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yulia Dodonova 165 127 82 77 66 5 277
Sergey Korolev 165 1.0× 126 1.0× 82 1.0× 77 1.0× 66 1.0× 4 274
Yechong Huang 148 0.9× 108 0.9× 84 1.0× 72 0.9× 79 1.2× 6 279
Wenyong Zhu 157 1.0× 164 1.3× 72 0.9× 82 1.1× 71 1.1× 5 322
Xinyan Zhao 121 0.7× 109 0.9× 73 0.9× 65 0.8× 39 0.6× 9 309
Jiahang Xu 114 0.7× 82 0.6× 68 0.8× 50 0.6× 50 0.8× 10 220
Marcia Hon 179 1.1× 131 1.0× 73 0.9× 70 0.9× 43 0.7× 2 277
Rooh Ullah Khan 115 0.7× 93 0.7× 67 0.8× 50 0.6× 30 0.5× 5 269
Shangran Qiu 73 0.4× 90 0.7× 43 0.5× 40 0.5× 54 0.8× 9 266
Nagaraj Yamanakkanavar 158 1.0× 104 0.8× 31 0.4× 141 1.8× 75 1.1× 10 314
Manan Binth Taj Noor 93 0.6× 86 0.7× 27 0.3× 47 0.6× 51 0.8× 4 284

Countries citing papers authored by Yulia Dodonova

Since Specialization
Citations

This map shows the geographic impact of Yulia Dodonova'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 Yulia Dodonova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yulia Dodonova more than expected).

Fields of papers citing papers by Yulia Dodonova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yulia Dodonova. 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 Yulia Dodonova. The network helps show where Yulia Dodonova may publish in the future.

Co-authorship network of co-authors of Yulia Dodonova

This figure shows the co-authorship network connecting the top 25 collaborators of Yulia Dodonova. A scholar is included among the top collaborators of Yulia Dodonova 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 Yulia Dodonova. Yulia Dodonova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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