Miyuki Wada

15 total papers · 615 total citations
14 papers, 495 citations indexed

About

Miyuki Wada is a scholar working on Cellular and Molecular Neuroscience, Biochemistry and Molecular Biology. According to data from OpenAlex, Miyuki Wada has authored 14 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cellular and Molecular Neuroscience, 5 papers in Biochemistry and 4 papers in Molecular Biology. Recurrent topics in Miyuki Wada's work include Neuroscience and Neuropharmacology Research (9 papers), Amino Acid Enzymes and Metabolism (5 papers) and Drug Transport and Resistance Mechanisms (3 papers). Miyuki Wada is often cited by papers focused on Neuroscience and Neuropharmacology Research (9 papers), Amino Acid Enzymes and Metabolism (5 papers) and Drug Transport and Resistance Mechanisms (3 papers). Miyuki Wada collaborates with scholars based in Japan and United States. Miyuki Wada's co-authors include Takuya Fujita, Akira Yamamoto, Naoki Okada, Tomonori Shinya, Hanae Kaku, Naoto Shibuya, Vadivel Ganapathy, Michiko Oka, Yoshinori Itoh and Qiang Wu and has published in prestigious journals such as Brain Research, Biochemical and Biophysical Research Communications and FEBS Letters.

In The Last Decade

Miyuki Wada

14 papers receiving 485 citations

Author Peers

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

Author						Papers	Cites
Miyuki Wada	165	158	131	98	77	14	495
Malcolm P. Seville	119 0.7×	71 0.4×	133 1.0×	17 0.2×	87 1.1×	9	447
Zongmin Li	283 1.7×	120 0.8×	37 0.3×	62 0.6×	36 0.5×	13	470
Karnire S. Pai	263 1.6×	32 0.2×	112 0.9×	38 0.4×	62 0.8×	15	501
Christine M. Beiswanger	182 1.1×	26 0.2×	76 0.6×	89 0.9×	73 0.9×	22	466
Jack P. Smith	320 1.9×	15 0.1×	149 1.1×	77 0.8×	91 1.2×	23	478
Nadine Urquhart	205 1.2×	27 0.2×	131 1.0×	91 0.9×	128 1.7×	15	549
María Burgal	157 1.0×	14 0.1×	98 0.7×	33 0.3×	53 0.7×	13	409
M. Fujiwara	251 1.5×	36 0.2×	87 0.7×	24 0.2×	71 0.9×	17	508
T Takenawa	287 1.7×	30 0.2×	32 0.2×	69 0.7×	112 1.5×	14	505
Françoise Esclaire	192 1.2×	43 0.3×	110 0.8×	17 0.2×	135 1.8×	12	443

Countries citing papers authored by Miyuki Wada

Since Specialization

Citations

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

Fields of papers citing papers by Miyuki Wada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miyuki Wada

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