Nobuyo Maeda

976 total citations
13 papers, 779 citations indexed

About

Nobuyo Maeda is a scholar working on Cell Biology, Surgery and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Nobuyo Maeda has authored 13 papers receiving a total of 779 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cell Biology, 3 papers in Surgery and 3 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Nobuyo Maeda's work include Heart Failure Treatment and Management (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Neurogenesis and neuroplasticity mechanisms (2 papers). Nobuyo Maeda is often cited by papers focused on Heart Failure Treatment and Management (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Neurogenesis and neuroplasticity mechanisms (2 papers). Nobuyo Maeda collaborates with scholars based in United States, Japan and France. Nobuyo Maeda's co-authors include Patrick M. Sullivan, Masahiko Watanabe, Steven H. Quarfordt, Michael K. Altenburg, Christopher W. Knouff, Myron E. Hinsdale, Hafid Mezdour, Gregg E. Homanics, Jayme Borensztajn and Howard Wong and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Journal of Neuroscience.

In The Last Decade

Nobuyo Maeda

10 papers receiving 763 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nobuyo Maeda United States 8 269 196 157 143 135 13 779
Christine Bétard Canada 21 445 1.7× 253 1.3× 239 1.5× 46 0.3× 141 1.0× 22 1.1k
Olga V. Savinova United States 17 661 2.5× 132 0.7× 134 0.9× 42 0.3× 252 1.9× 31 1.4k
Rita P. S. Middelberg Australia 12 251 0.9× 150 0.8× 139 0.9× 62 0.4× 167 1.2× 18 797
Christina Leibrock Germany 17 350 1.3× 93 0.5× 95 0.6× 55 0.4× 117 0.9× 25 932
Ranjana Poddar United States 18 425 1.6× 126 0.6× 113 0.7× 423 3.0× 50 0.4× 29 1.2k
Elena Beltramo Italy 20 424 1.6× 65 0.3× 126 0.8× 82 0.6× 238 1.8× 39 1.3k
Petter Vikman Sweden 19 477 1.8× 299 1.5× 258 1.6× 25 0.2× 217 1.6× 25 1.1k
S Mori Japan 11 282 1.0× 239 1.2× 301 1.9× 26 0.2× 183 1.4× 21 903
Z. Li China 7 396 1.5× 118 0.6× 315 2.0× 64 0.4× 124 0.9× 14 936
Takatoshi Saito Japan 14 438 1.6× 119 0.6× 170 1.1× 23 0.2× 122 0.9× 28 824

Countries citing papers authored by Nobuyo Maeda

Since Specialization
Citations

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

Fields of papers citing papers by Nobuyo Maeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nobuyo Maeda

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

All Works

13 of 13 papers shown
1.
Smithies, Oliver, Seigo Hatada, William A. Kuziel, & Nobuyo Maeda. (2021). The Influence of Chromosomal Location on the Expression of Two Transgenes in Mice. UNC Libraries.
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3.
Gebre, Abraham K., Jenelle M. Timmins, Elena Boudyguina, et al.. (2020). Increased Cellular Free Cholesterol in Macrophage-specific Abca1 Knock-out Mice Enhances Pro-inflammatory Response of Macrophages. UNC Libraries. 2 indexed citations
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Goy, Michael F., Paula M. Oliver, Joshua W. Knowles, et al.. (2001). Evidence for a novel natriuretic peptide receptor that prefers brain natriuretic peptide over atrial natriuretic peptide. Biochemical Journal. 358(2). 379–387. 26 indexed citations
7.
Goy, Michael F., Paula M. Oliver, Joshua W. Knowles, et al.. (2001). Evidence for a novel natriuretic peptide receptor that prefers brain natriuretic peptide over atrial natriuretic peptide. Biochemical Journal. 358(2). 379–379. 35 indexed citations
8.
Knouff, Christopher W., Myron E. Hinsdale, Hafid Mezdour, et al.. (1999). Apo E structure determines VLDL clearance and atherosclerosis risk in mice. Journal of Clinical Investigation. 103(11). 1579–1586. 254 indexed citations
9.
Aratani, Yasuaki, et al.. (1999). Severe Impairment in Early Host Defense againstCandida albicans in Mice Deficient in Myeloperoxidase. Infection and Immunity. 67(4). 1828–1836. 8 indexed citations
10.
Fujita, Nobuya, April Kemper, Jeffrey L. Dupree, et al.. (1998). The Cytoplasmic Domain of the Large Myelin-Associated Glycoprotein Isoform Is Needed for Proper CNS But Not Peripheral Nervous System Myelination. Journal of Neuroscience. 18(6). 1970–1978. 70 indexed citations
11.
Maeda, Nobuyo, et al.. (1998). Characterization of the stress-inducing effects of homocysteine. Biochemical Journal. 332(1). 213–221. 198 indexed citations
12.
Homanics, Gregg E., Jesús Osada, Sunny H. Zhang, et al.. (1995). Mild Dyslipidemia in Mice following Targeted Inactivation of the Hepatic Lipase Gene. Journal of Biological Chemistry. 270(7). 2974–2980. 175 indexed citations
13.
Erickson, Laurie & Nobuyo Maeda. (1994). Parallel Evolutionary Events in the Haptoglobin Gene Clusters of Rhesus Monkey and Human. Genomics. 22(3). 579–589. 9 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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