Pam Kurimoto

643 total citations
8 papers, 410 citations indexed

About

Pam Kurimoto is a scholar working on Molecular Biology, Oncology and Orthopedics and Sports Medicine. According to data from OpenAlex, Pam Kurimoto has authored 8 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Oncology and 4 papers in Orthopedics and Sports Medicine. Recurrent topics in Pam Kurimoto's work include Bone health and treatments (4 papers), Bone health and osteoporosis research (4 papers) and Bone Metabolism and Diseases (4 papers). Pam Kurimoto is often cited by papers focused on Bone health and treatments (4 papers), Bone health and osteoporosis research (4 papers) and Bone Metabolism and Diseases (4 papers). Pam Kurimoto collaborates with scholars based in United States, United Kingdom and China. Pam Kurimoto's co-authors include Bernard P. Halloran, Benjamin Boudignon, Jay Cao, Thomas J. Wronski, Urszula T. Iwaniec, Sharmila Majumdar, Andrew J. Burghardt, Qing‐Tian Niu, Paul J. Kostenuik and Michael S. Ominsky and has published in prestigious journals such as Journal of Applied Physiology, Journal of Bone and Mineral Research and Journal of Dental Research.

In The Last Decade

Pam Kurimoto

8 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pam Kurimoto United States	7	262	131	127	67	43	8	410
Cielo Barragan‐Adjemian United States	5	227 0.9×	128 1.0×	137 1.1×	91 1.4×	28 0.7×	5	408
LeAnn M. Tiede-Lewis United States	9	277 1.1×	168 1.3×	92 0.7×	67 1.0×	48 1.1×	14	442
Forest Lai United States	7	311 1.2×	148 1.1×	189 1.5×	60 0.9×	85 2.0×	7	497
Genki Kato Japan	4	333 1.3×	96 0.7×	189 1.5×	80 1.2×	19 0.4×	6	468
Saja Al‐Dujaili United States	5	164 0.6×	115 0.9×	74 0.6×	35 0.5×	44 1.0×	10	357
Mari Nakagawa Japan	7	263 1.0×	39 0.3×	172 1.4×	79 1.2×	67 1.6×	12	570
Pia Rosgaard Jensen Denmark	9	218 0.8×	165 1.3×	174 1.4×	49 0.7×	19 0.4×	12	362
Yin-Ji Li Japan	9	228 0.9×	53 0.4×	105 0.8×	46 0.7×	26 0.6×	11	411
Zohreh Khavandgar Canada	9	194 0.7×	40 0.3×	41 0.3×	54 0.8×	42 1.0×	15	366
Danese M. Joiner United States	10	334 1.3×	89 0.7×	111 0.9×	65 1.0×	26 0.6×	11	491

Countries citing papers authored by Pam Kurimoto

Since Specialization

Citations

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

Fields of papers citing papers by Pam Kurimoto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pam Kurimoto

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Kurimoto, Pam, Qing‐Tian Niu, Marina Stolina, et al.. (2018). Sclerostin and DKK1 Inhibition Preserves and Augments Alveolar Bone Volume and Architecture in Rats with Alveolar Bone Loss. Journal of Dental Research. 97(9). 1031–1038. 41 indexed citations

2.

Stolina, Marina, Denise Dwyer, Qing‐Tian Niu, et al.. (2014). Temporal changes in systemic and local expression of bone turnover markers during six months of sclerostin antibody administration to ovariectomized rats. Bone. 67. 305–313. 74 indexed citations

3.

Shahnazari, Mohammad, Pam Kurimoto, Benjamin Boudignon, et al.. (2012). Simulated spaceflight produces a rapid and sustained loss of osteoprogenitors and an acute but transitory rise of osteoclast precursors in two genetic strains of mice. American Journal of Physiology-Endocrinology and Metabolism. 303(11). E1354–E1362. 15 indexed citations

4.

Han, Xianglong, Yinshi Ren, Pam Kurimoto, et al.. (2011). Post-natal Effect of Overexpressed DKK1 on Mandibular Molar Formation. Journal of Dental Research. 90(11). 1312–1317. 46 indexed citations

5.

Boudignon, Benjamin, Daniel D. Bikle, Pam Kurimoto, et al.. (2007). Insulin-like growth factor I stimulates recovery of bone lost after a period of skeletal unloading. Journal of Applied Physiology. 103(1). 125–131. 25 indexed citations

6.

Cao, Jay, Patrick A. Singleton, Sharmila Majumdar, et al.. (2005). Hyaluronan Increases RANKL Expression in Bone Marrow Stromal Cells Through CD44. Journal of Bone and Mineral Research. 20(1). 30–40. 6 indexed citations

7.

Cao, Jay, Thomas J. Wronski, Urszula T. Iwaniec, et al.. (2005). Aging Increases Stromal/Osteoblastic Cell-Induced Osteoclastogenesis and Alters the Osteoclast Precursor Pool in the Mouse. Journal of Bone and Mineral Research. 20(9). 1659–1668. 143 indexed citations

8.

Cao, Jay, Patrick A. Singleton, Sharmila Majumdar, et al.. (2005). Hyaluronan Increases RANKL Expression in Bone Marrow Stromal Cells Through CD44. Journal of Bone and Mineral Research. 20(1). 30–40. 60 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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