U Mami

471 total citations
9 papers, 309 citations indexed

About

U Mami is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Immunology. According to data from OpenAlex, U Mami has authored 9 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Cellular and Molecular Neuroscience and 2 papers in Immunology. Recurrent topics in U Mami's work include Cell death mechanisms and regulation (2 papers), Toxin Mechanisms and Immunotoxins (1 paper) and Acute Myeloid Leukemia Research (1 paper). U Mami is often cited by papers focused on Cell death mechanisms and regulation (2 papers), Toxin Mechanisms and Immunotoxins (1 paper) and Acute Myeloid Leukemia Research (1 paper). U Mami collaborates with scholars based in Japan, United States and China. U Mami's co-authors include Masao Yamada, Yoshiaki Shikama, Toshiyuki Miyashita, Aya Yoshida, Tomomi Shimogori, Satomi Kikuchi, Masaharu Ogawa, Yuji Sugita, Masao Yamada and John C. Reed and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Analytical Biochemistry.

In The Last Decade

U Mami

9 papers receiving 301 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
U Mami Japan 8 202 92 52 42 37 9 309
Ken Matsuura Japan 8 257 1.3× 65 0.7× 44 0.8× 29 0.7× 24 0.6× 11 383
Andrew Cluster United States 7 165 0.8× 112 1.2× 37 0.7× 19 0.5× 11 0.3× 20 340
Tokuichi Iguchi Japan 10 303 1.5× 123 1.3× 32 0.6× 45 1.1× 10 0.3× 17 451
Laura A. Bell United States 9 221 1.1× 83 0.9× 19 0.4× 101 2.4× 55 1.5× 13 337
Leila Haery United States 6 314 1.6× 55 0.6× 52 1.0× 83 2.0× 20 0.5× 7 433
Silvia Messali Italy 7 265 1.3× 75 0.8× 78 1.5× 28 0.7× 7 0.2× 10 381
Nicola Micali United States 10 277 1.4× 34 0.4× 20 0.4× 27 0.6× 39 1.1× 11 380
Javier García‐Ceca Spain 13 147 0.7× 251 2.7× 72 1.4× 23 0.5× 11 0.3× 27 380
Zintis Inde United States 8 129 0.6× 40 0.4× 32 0.6× 65 1.5× 10 0.3× 9 224
Masafumi Ohtsubo Japan 4 178 0.9× 25 0.3× 34 0.7× 39 0.9× 19 0.5× 4 260

Countries citing papers authored by U Mami

Since Specialization
Citations

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

Fields of papers citing papers by U Mami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of U Mami

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

All Works

9 of 9 papers shown
1.
Kita, Yoshiaki, Yan Wang, Tsutomu Hashikawa, et al.. (2021). Cellular-resolution gene expression profiling in the neonatal marmoset brain reveals dynamic species- and region-specific differences. Proceedings of the National Academy of Sciences. 118(18). 19 indexed citations
2.
Yoshida, Aya, et al.. (2013). BTBD3 Controls Dendrite Orientation Toward Active Axons in Mammalian Neocortex. Science. 342(6162). 1114–1118. 76 indexed citations
3.
Lee, Kyoung‐Youl, Makoto Shibutani, Kaoru Inoue, et al.. (2006). Methacarn fixation—effects of tissue processing and storage conditions on detection of mRNAs and proteins in paraffin-embedded tissues. Analytical Biochemistry. 351(1). 36–43. 17 indexed citations
4.
Fujimoto, Hitoshi, Makoto Shibutani, Kaoru Inoue, et al.. (2006). A Case Report of a Spontaneous Gastrointestinal Stromal Tumor (GIST) Occurring in a F344 Rat. Toxicologic Pathology. 34(2). 164–167. 13 indexed citations
5.
Wu, Zhenghong, Lisong Shen, Yuka Inatomi, et al.. (2003). Effects of TNFα on the growth and sensitivity to cytosine arabinoside of blast progenitors in acute myelogenous leukemia with special reference to the role of NF-κB. Leukemia Research. 27(11). 1009–1018. 1 indexed citations
6.
Yoshida, Ning Lu, Toshiyuki Miyashita, U Mami, et al.. (2002). Analysis of gene expression patterns during glucocorticoid-induced apoptosis using oligonucleotide arrays. Biochemical and Biophysical Research Communications. 293(4). 1254–1261. 65 indexed citations
7.
Shikama, Yoshiaki, et al.. (2001). Comprehensive Studies on Subcellular Localizations and Cell Death-Inducing Activities of Eight GFP-Tagged Apoptosis-Related Caspases. Experimental Cell Research. 264(2). 315–325. 62 indexed citations
8.
Miyashita, Toshiyuki, Jun Matsui, U Mami, et al.. (1999). Expression of Extended Polyglutamine Sequentially Activates Initiator and Effector Caspases. Biochemical and Biophysical Research Communications. 257(3). 724–730. 37 indexed citations
9.
Mami, U, et al.. (1997). Bcl-2 Relieves the Trans-Repressive Function of the Glucocorticoid Receptor and Inhibits the Activation of CPP32-like Cysteine Proteases. Biochemical and Biophysical Research Communications. 233(3). 781–787. 19 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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