Mika Kikkawa

818 citations
22 papers · 620 indexed · h-index 13
Topics
Renal cell carcinoma treatment (6 papers)Tuberous Sclerosis Complex Research (4 papers)Renal and related cancers (4 papers)
Partner nations
JapanUnited StatesCanada

In The Last Decade

Mika Kikkawa

22 papers receiving 613 citations

Peers

Mika Kikkawa
Comparison fields: 5 of 69
  • Molecular Biology 284
  • Pulmonary and Respiratory Medicine 281
  • Physiology 184
  • Genetics 102
  • Nephrology 55
Replace Dominic J. Ciavatta with:
Dominic J. Ciavatta United States
Rosalind C. Williamson United Kingdom
Mohammad Azam India
Anne L. Hancock United Kingdom
Maria De Angioletti Italy
Nicole Lucien France
Rui Min China
Manuel Rosa‐Garrido United States
Sunita Patel United States
Scott Langdon United States
Mika Kikkawa relative to Dominic J. Ciavatta United States Dominic J. Ciavatta's profile →
Citations per field
00.5×1.6×
Dominic J. Ciavatta · 1×
Citations per year

Countries citing papers authored by Mika Kikkawa

Since Specialization
Citations

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

Fields of papers citing papers by Mika Kikkawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mika Kikkawa

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 11
2 39
3 43
4 12
5 12
6 20
7 10
8 7
9 2
10 52
11 3
12 114
13 106
14 4
15 1
16 36
17 52
18
Two-step induction of primitive erythrocytes in Xenopus laevis embryos: signals from the vegetal endoderm and the overlying ectoderm.
23
19 27
20 3

About Mika Kikkawa

Mika Kikkawa is a scholar working on Nephrology, Hematology and Pulmonary and Respiratory Medicine, having authored 22 papers that have together received 620 indexed citations. Recurring topics across this work include Renal cell carcinoma treatment (6 papers), Tuberous Sclerosis Complex Research (4 papers) and Renal and related cancers (4 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (281 citations), Nephrology (55 citations) and Physiology (184 citations). Mika Kikkawa has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Kuniaki Seyama, Makiko Kunogi, Kazuhisa Takahashi, Shin‐ichiro Iwakami, Hikari Taka, Toshio Kumasaka, Masatoshi Kurihara, Kazunori Tobino, Tsutomu Fujimura and Reiko Mineki. Their work appears in journals such as Blood, PLoS ONE and Molecular and Cellular Biology.

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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