Mamiko Noda

2.9k citations
8 papers · 2.2k indexed · 1 hit paper · h-index 7
Topics
Chemokine receptors and signaling (5 papers)Immunotherapy and Immune Responses (2 papers)T-cell and B-cell Immunology (2 papers)

In The Last Decade

Mamiko Noda

8 papers receiving 2.2k citations

Hit Papers

Maintenance of the Hematopoietic Stem Cell Pool by CXCL12...2006202620122019200650010001.5k

Peers

Mamiko Noda
Comparison fields: 5 of 85
  • Hematology 1.2k
  • Immunology 944
  • Oncology 631
  • Genetics 611
  • Molecular Biology 610
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Matthew Christopher United States
Adam Greenbaum United States
Osman Yılmaz United States
Joji Fujisaki United States
Jeff Haug United States
Roderick P. Martin United States
Ryan B. Day United States
Bianca Nowlan Australia
Abel Sánchez‐Aguilera Spain
Gabriela Oser Switzerland
Mamiko Noda relative to Matthew Christopher United States Matthew Christopher's profile →
Citations per field
00.5×1.5×
Matthew Christopher · 1×
Citations per year

Countries citing papers authored by Mamiko Noda

Since Specialization
Citations

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

Fields of papers citing papers by Mamiko Noda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mamiko Noda

This figure shows the co-authorship network connecting the top 25 collaborators of Mamiko Noda. A scholar is included among the top collaborators of Mamiko Noda 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 Mamiko Noda. Mamiko Noda 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
#WorkIndexed citations
1 6
2 76
3 101
4 42
5 117
6 5
7 69
8
Maintenance of the Hematopoietic Stem Cell Pool by CXCL12-CXCR4 Chemokine Signaling in Bone Marrow Stromal Cell Nichesbreakdown →
1796

About Mamiko Noda

Mamiko Noda is a scholar working on Linguistics and Language, Immunology and Oncology, having authored 8 papers that have together received 2.2k indexed citations. Recurring topics across this work include Chemokine receptors and signaling (5 papers), Immunotherapy and Immune Responses (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Hematology (1.2k citations), Genetics (611 citations) and Immunology (944 citations). Mamiko Noda has collaborated with scholars based in Japan, United Kingdom and Pakistan. Frequent co-authors include Takashi Nagasawa, Tatsuki Sugiyama, Hiroshi Kohara, Yoshiki Omatsu, Nobutaka Fujii, Michelle L. Janas, Martin Turner, Gabriele Varano, Kristjan S. Gudmundsson and Shinya Oishi. Their work appears in journals such as Nucleic Acids Research, The Journal of Experimental Medicine and Blood.

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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