Youn Na

9 total papers · 667 total citations
6 papers, 514 citations indexed

About

Youn Na is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Youn Na has authored 6 papers receiving a total of 514 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Cognitive Neuroscience. Recurrent topics in Youn Na's work include Neuroscience and Neuropharmacology Research (3 papers), Photoreceptor and optogenetics research (2 papers) and Angiogenesis and VEGF in Cancer (1 paper). Youn Na is often cited by papers focused on Neuroscience and Neuropharmacology Research (3 papers), Photoreceptor and optogenetics research (2 papers) and Angiogenesis and VEGF in Cancer (1 paper). Youn Na collaborates with scholars based in United States, Belgium and South Korea. Youn Na's co-authors include Paul Worley, Richard L. Huganir, Dietmar Kuhl, Jean-Claude Béïque, Yi Zhou, Hiroaki Okuyama, Jacob Wesley, Yuval Shaked, Gregg L. Semenza and Hideo Kimura and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Molecular Cell.

In The Last Decade

Youn Na

6 papers receiving 510 citations

Author Peers

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

Author						Papers	Cites
Youn Na	278	169	130	71	65	6	514
Lai-Man N. Wu	293 1.1×	169 1.0×	81 0.6×	80 1.1×	34 0.5×	8	503
Georgia Kouroupi	357 1.3×	211 1.2×	85 0.7×	62 0.9×	60 0.9×	16	609
Gennaro Andolfi	375 1.3×	134 0.8×	69 0.5×	78 1.1×	40 0.6×	18	530
Lindsay McGuinness	224 0.8×	217 1.3×	43 0.3×	56 0.8×	74 1.1×	8	501
Laurie R. Earls	371 1.3×	143 0.8×	93 0.7×	97 1.4×	31 0.5×	12	485
Da‐Thao Tran	295 1.1×	84 0.5×	104 0.8×	37 0.5×	31 0.5×	8	606
Małgorzata Perycz	355 1.3×	144 0.9×	44 0.3×	104 1.5×	89 1.4×	13	544
Marita Meins	287 1.0×	145 0.9×	181 1.4×	85 1.2×	62 1.0×	10	619
Samuel S. Ng	382 1.4×	101 0.6×	268 2.1×	48 0.7×	25 0.4×	13	583
Annarita De Luca	314 1.1×	72 0.4×	73 0.6×	80 1.1×	19 0.3×	9	459

Countries citing papers authored by Youn Na

Since Specialization

Citations

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

Fields of papers citing papers by Youn Na

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Youn Na

This figure shows the co-authorship network connecting the top 25 collaborators of Youn Na. A scholar is included among the top collaborators of Youn Na 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 Youn Na. Youn Na 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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