Kuniko Ishikawa

894 total citations
8 papers, 725 citations indexed

About

Kuniko Ishikawa is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Kuniko Ishikawa has authored 8 papers receiving a total of 725 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 4 papers in Physiology. Recurrent topics in Kuniko Ishikawa's work include Pain Mechanisms and Treatments (4 papers), Ion channel regulation and function (3 papers) and Neuroscience and Neural Engineering (3 papers). Kuniko Ishikawa is often cited by papers focused on Pain Mechanisms and Treatments (4 papers), Ion channel regulation and function (3 papers) and Neuroscience and Neural Engineering (3 papers). Kuniko Ishikawa collaborates with scholars based in United States and Japan. Kuniko Ishikawa's co-authors include Joel A. Black, Stephen G. Waxman, Jeffery D. Kocsis, Ikuhide Kohama, Theodore Cummins, Masaki Tanaka, Sulayman D. Dib‐Hajj, Masaki Tanaka, Stephen G. Waxman and Johnathan J. Nau and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and The Journal of Cell Biology.

In The Last Decade

Kuniko Ishikawa

8 papers receiving 704 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kuniko Ishikawa United States 8 427 410 303 111 81 8 725
Fay Heblich United Kingdom 7 288 0.7× 575 1.4× 419 1.4× 69 0.6× 61 0.8× 9 855
H. Baba Japan 12 447 1.0× 239 0.6× 315 1.0× 85 0.8× 30 0.4× 28 739
W. N. Hormuzdiar United States 6 454 1.1× 449 1.1× 352 1.2× 124 1.1× 19 0.2× 6 679
D. M. White Australia 17 523 1.2× 196 0.5× 426 1.4× 86 0.8× 24 0.3× 27 759
Lucy Bee United Kingdom 12 673 1.6× 323 0.8× 245 0.8× 75 0.7× 24 0.3× 14 915
Meei‐Ling Tsaur Taiwan 12 265 0.6× 221 0.5× 215 0.7× 50 0.5× 23 0.3× 19 431
C. Rivero‐Melián Sweden 7 354 0.8× 112 0.3× 357 1.2× 57 0.5× 23 0.3× 10 578
Elda Tzoumaka United States 6 442 1.0× 516 1.3× 358 1.2× 118 1.1× 14 0.2× 7 780
C. De Felipe Spain 11 216 0.5× 321 0.8× 474 1.6× 22 0.2× 29 0.4× 13 750
Shuqin Zong Japan 15 217 0.5× 438 1.1× 366 1.2× 43 0.4× 17 0.2× 21 675

Countries citing papers authored by Kuniko Ishikawa

Since Specialization
Citations

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

Fields of papers citing papers by Kuniko Ishikawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kuniko Ishikawa

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

All Works

8 of 8 papers shown
1.
Kono, Satoshi, Hitoshi Suzuki, Toshiaki Oda, et al.. (2006). Biochemical Features of Ceruloplasmin Gene Mutations Linked to Aceruloplasminemia. NeuroMolecular Medicine. 8(3). 361–374. 14 indexed citations
2.
Ishikawa, Kuniko, Natalie L. Catlett, Jennifer L. Novak, et al.. (2003). Identification of an organelle-specific myosin V receptor. The Journal of Cell Biology. 160(6). 887–897. 96 indexed citations
3.
Kohama, Ikuhide, Kuniko Ishikawa, & Jeffery D. Kocsis. (2000). Synaptic reorganization in the substantia gelatinosa after peripheral nerve neuroma formation: aberrant innervation of lamina II neurons by Abeta afferents.. PubMed. 20(4). 1538–49. 90 indexed citations
4.
Kohama, Ikuhide, Kuniko Ishikawa, & Jeffery D. Kocsis. (2000). Synaptic Reorganization in the Substantia Gelatinosa After Peripheral Nerve Neuroma Formation: Aberrant Innervation of Lamina II Neurons by Aβ Afferents. Journal of Neuroscience. 20(4). 1538–1549. 78 indexed citations
5.
Ishikawa, Kuniko, Masaki Tanaka, Joel A. Black, & Stephen G. Waxman. (1999). Changes in expression of voltage-gated potassium channels in dorsal root ganglion neurons following axotomy. Muscle & Nerve. 22(4). 502–507. 148 indexed citations
6.
Tanaka, Masaki, Theodore Cummins, Kuniko Ishikawa, et al.. (1999). Molecular and functional remodeling of electrogenic membrane of hypothalamic neurons in response to changes in their input. Proceedings of the National Academy of Sciences. 96(3). 1088–1093. 68 indexed citations
7.
Tanaka, Masaki, Theodore Cummins, Kuniko Ishikawa, et al.. (1998). SNS Na+ channel expression increases in dorsal root ganglion neurons in the carrageenan inflammatory pain model. Neuroreport. 9(6). 967–972. 190 indexed citations
8.
Dib‐Hajj, Sulayman D., Kuniko Ishikawa, Theodore Cummins, & Stephen G. Waxman. (1997). Insertion of a SNS‐specific tetrapeptide in S3–S4 linker of D4 accelerates recovery from inactivation of skeletal muscle voltage‐gated Na channel μ1 in HEK293 cells. FEBS Letters. 416(1). 11–14. 41 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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2026