Mami Ishida

807 citations
36 papers · 659 · h-index 15

Impact in

Papers in

Mami Ishida

33 papers receiving 644 citations

Peers

Mami Ishida
Comparison fields: 5 of 90
  • Developmental Neuroscience 135
  • Cellular and Molecular Neuroscience 269
  • Cognitive Neuroscience 109
  • Sensory Systems 23
  • Molecular Biology 282
Replace Jeffrey J. Petrozzino with:
Jeffrey J. Petrozzino United States
Béatrice Cholley France
Jost Leemhuis Germany
Ru Feng China
Rachel S. Greenberg United States
Т. С. Калинина Russia
Kathleen L. Rubino United States
Gail Lewandowski United States
Jean‐Louis Bossu France
José S. Aguilar United States
Mami Ishida relative to Jeffrey J. Petrozzino United States Jeffrey J. Petrozzino's profile →
Citations per field
00.5×2×2.8×
Jeffrey J. Petrozzino · 1×
Citations per year

Countries citing papers authored by Mami Ishida

Since Specialization
Citations

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

Fields of papers citing papers by Mami Ishida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mami Ishida, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mami Ishida Line = papers co-authored together Mami Ishida links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200382
2 200861
3 199155
4 200946
5 199945
6 199437
7 199936
8 201535
9 200331
10 200229
11 202026
12 199825
13 199824
14 200818
15 200616
16 200512
17 200910
18 20239
19 20098
20 20128

About Mami Ishida

Mami Ishida is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Nephrology, Developmental Neuroscience and Physiology, having authored 36 papers that have together received 659 indexed citations. Recurring topics across this work include Axon Guidance and Neuronal Signaling (8 papers), Neurogenesis and neuroplasticity mechanisms (6 papers), Neuroscience and Neuropharmacology Research (6 papers), Renal Diseases and Glomerulopathies (5 papers), Glycosylation and Glycoproteins Research (2 papers), Genetics and Neurodevelopmental Disorders (2 papers), Antifungal resistance and susceptibility (2 papers) and Congenital heart defects research (2 papers). The work is most often cited by research in Developmental Neuroscience (135 citations), Cellular and Molecular Neuroscience (269 citations), Cognitive Neuroscience (109 citations), Sensory Systems (23 citations) and Molecular Biology (282 citations). Mami Ishida has collaborated with scholars based in Japan, Taiwan and United States. Frequent co-authors include Yasuyoshi Arimatsu, Hiroshi Takahashi, Kaoru Takahashi, Sachiyo Ichinose, Akira Omori, Takeshi Kaneko, Hajime Komano, Wan-Zhu Bai, Keiko Takiguchi‐Hayashi and Yoshihiko Uratani. Their work appears in journals such as Neuroscience, Brain Research, Biochemical and Biophysical Research Communications, Infection and Immunity and Cancer Control.

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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