Miyako Abe

2.1k total citations · 1 hit paper
20 papers, 1.7k citations indexed

About

Miyako Abe is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Nutrition and Dietetics. According to data from OpenAlex, Miyako Abe has authored 20 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 9 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Nutrition and Dietetics. Recurrent topics in Miyako Abe's work include Glycosylation and Glycoproteins Research (10 papers), Monoclonal and Polyclonal Antibodies Research (8 papers) and Infant Nutrition and Health (3 papers). Miyako Abe is often cited by papers focused on Glycosylation and Glycoproteins Research (10 papers), Monoclonal and Polyclonal Antibodies Research (8 papers) and Infant Nutrition and Health (3 papers). Miyako Abe collaborates with scholars based in United States, Japan and Spain. Miyako Abe's co-authors include Donald Küfe, Daniel F. Hayes, Jeffrey Schlom, Giorgio Inghirami, Javed Siddiqui, Eilon Shani, E.J. Yunis, Tsuneya Ohno, Hiroshi Sekine and Kristen A. Keefe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Journal of Clinical Oncology.

In The Last Decade

Miyako Abe

20 papers receiving 1.7k citations

Hit Papers

Differential Reactivity of a Novel Monoclonal Antibody (D... 1984 2026 1998 2012 1984 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Miyako Abe United States 17 1.3k 624 482 473 195 20 1.7k
M Błaszczyk United States 16 1.0k 0.8× 678 1.1× 402 0.8× 202 0.4× 90 0.5× 29 1.4k
Nigel Peat United Kingdom 6 1.2k 0.9× 454 0.7× 540 1.1× 273 0.6× 109 0.6× 6 1.4k
David V. Gold United States 29 936 0.7× 637 1.0× 431 0.9× 883 1.9× 64 0.3× 67 2.0k
Luis E. Fernández Cuba 31 1.1k 0.9× 577 0.9× 1.3k 2.7× 544 1.2× 85 0.4× 70 2.2k
Leia M. Smith United States 21 893 0.7× 535 0.9× 416 0.9× 830 1.8× 170 0.9× 31 1.9k
Jenny J. L. Ho United States 19 855 0.7× 290 0.5× 284 0.6× 488 1.0× 59 0.3× 40 1.3k
Cinda M. Boyer United States 18 620 0.5× 355 0.6× 656 1.4× 537 1.1× 93 0.5× 31 1.5k
Lee H. Pai United States 24 599 0.5× 699 1.1× 766 1.6× 392 0.8× 101 0.5× 37 1.8k
Nancy A. Cochran United States 10 852 0.7× 265 0.4× 543 1.1× 110 0.2× 227 1.2× 11 1.5k
Brian G. Van Ness United States 24 1.2k 1.0× 306 0.5× 936 1.9× 405 0.9× 151 0.8× 68 2.1k

Countries citing papers authored by Miyako Abe

Since Specialization
Citations

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

Fields of papers citing papers by Miyako Abe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miyako Abe

This figure shows the co-authorship network connecting the top 25 collaborators of Miyako Abe. A scholar is included among the top collaborators of Miyako Abe 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 Miyako Abe. Miyako Abe 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
1.
Abe, Miyako, Wanling Xie, Meredith M. Regan, et al.. (2010). Single‐nucleotide polymorphisms within the antioxidant defence system and associations with aggressive prostate cancer. British Journal of Urology. 107(1). 126–134. 34 indexed citations
2.
Mucci, Lorelei A., Jennifer R. Rider, William D. Figg, et al.. (2009). Polymorphism in endostatin, an angiogenesis inhibitor, and prostate cancer risk and survival: A prospective study. International Journal of Cancer. 125(5). 1143–1146. 9 indexed citations
3.
Chan, June M., William Oh, Wanling Xie, et al.. (2009). Plasma Selenium, Manganese Superoxide Dismutase, and Intermediate- or High-Risk Prostate Cancer. Journal of Clinical Oncology. 27(22). 3577–3583. 47 indexed citations
4.
McIntyre, Matthew H., Philip W. Kantoff, Meir J. Stampfer, et al.. (2007). Prostate Cancer Risk and ESR1 TA, ESR2 CA Repeat Polymorphisms. Cancer Epidemiology Biomarkers & Prevention. 16(11). 2233–2236. 25 indexed citations
5.
7.
Manome, Yoshinobu, et al.. (1994). Enhancer sequences of the DF3 gene regulate expression of the herpes simplex virus thymidine kinase gene and confer sensitivity of human breast cancer cells to ganciclovir.. PubMed. 54(20). 5408–13. 68 indexed citations
8.
Abe, Miyako & Donald Küfe. (1993). Characterization of cis-acting elements regulating transcription of the human DF3 breast carcinoma-associated antigen (MUC1) gene.. Proceedings of the National Academy of Sciences. 90(1). 282–286. 106 indexed citations
9.
Saito, Hiroyuki, et al.. (1992). Isolation and characterization of the measles virus strains with low hemagglutination activity.. PubMed. 33(1). 57–60. 27 indexed citations
10.
Perey, Lucien, Daniel F. Hayes, Peter Maimonis, et al.. (1992). Tumor selective reactivity of a monoclonal antibody prepared against a recombinant peptide derived from the DF3 human breast carcinoma-associated antigen.. PubMed. 52(9). 2563–8. 89 indexed citations
11.
Abe, Miyako & D Kufe. (1990). Transcriptional regulation of DF3 gene expression in human MCF‐7 breast carcinoma cells. Journal of Cellular Physiology. 143(2). 226–231. 22 indexed citations
12.
Abe, Miyako, Javed Siddiqui, & Donald Küfe. (1989). Sequence analysis of the 5′ region of the human DF3 breast carcinoma-associated antigen gene. Biochemical and Biophysical Research Communications. 165(2). 644–649. 16 indexed citations
13.
Hull, Steven R., Allan J. Bright, K.L. Carraway, et al.. (1989). Oligosaccharide differences in the DF3 sialomucin antigen from normal human milk and the BT-20 human breast carcinoma cell line.. PubMed. 1(4). 261–7. 100 indexed citations
14.
Siddiqui, Javed, Miyako Abe, Daniel F. Hayes, et al.. (1988). Isolation and sequencing of a cDNA coding for the human DF3 breast carcinoma-associated antigen.. Proceedings of the National Academy of Sciences. 85(7). 2320–2323. 273 indexed citations
15.
Abe, Miyako & Donald Küfe. (1987). Identification of a family of high molecular weight tumor-associated glycoproteins.. The Journal of Immunology. 139(1). 257–261. 57 indexed citations
17.
Hayes, Daniel F., Hiroshi Sekine, Tsuneya Ohno, et al.. (1985). Use of a murine monoclonal antibody for detection of circulating plasma DF3 antigen levels in breast cancer patients.. Journal of Clinical Investigation. 75(5). 1671–1678. 175 indexed citations
18.
Küfe, Donald, et al.. (1984). Differential Reactivity of a Novel Monoclonal Antibody (DF3) with Human Malignant versus Benign Breast Tumors. Hybridoma. 3(3). 223–232. 480 indexed citations breakdown →
19.
Abe, Miyako & Donald Küfe. (1984). Sodium butyrate induction of milk-related antigens in human MCF-7 breast carcinoma cells.. PubMed. 44(10). 4574–7. 55 indexed citations
20.
Abe, Miyako & Donald Küfe. (1984). Effect of sodium butyrate on human breast carcinoma (MCF-7) cellular proliferation, morphology, and CEA production. Breast Cancer Research and Treatment. 4(4). 269–274. 26 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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