J. E. Wergedal

3.3k total citations
54 papers, 2.7k citations indexed

About

J. E. Wergedal is a scholar working on Molecular Biology, Orthopedics and Sports Medicine and Oncology. According to data from OpenAlex, J. E. Wergedal has authored 54 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 26 papers in Orthopedics and Sports Medicine and 18 papers in Oncology. Recurrent topics in J. E. Wergedal's work include Bone health and osteoporosis research (25 papers), Bone Metabolism and Diseases (18 papers) and Bone health and treatments (14 papers). J. E. Wergedal is often cited by papers focused on Bone health and osteoporosis research (25 papers), Bone Metabolism and Diseases (18 papers) and Bone health and treatments (14 papers). J. E. Wergedal collaborates with scholars based in United States, Austria and Germany. J. E. Wergedal's co-authors include David J. Baylink, David J. Baylink, Subburaman Mohan, M. Stauffer, K.‐H. William Lau, D J Baylink, Charles L. Rich, Wesley G. Beamer, Jonathan Farley and Frederick R. Singer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

J. E. Wergedal

53 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. E. Wergedal United States 30 1.2k 839 681 650 407 54 2.7k
D J Baylink United States 22 803 0.7× 491 0.6× 645 0.9× 346 0.5× 325 0.8× 45 2.0k
Romain Dacquin France 12 1.3k 1.1× 823 1.0× 572 0.8× 623 1.0× 306 0.8× 13 2.8k
Anne M. Delany United States 36 2.5k 2.1× 681 0.8× 535 0.8× 943 1.5× 426 1.0× 68 4.2k
Christelle Desbois France 10 1.1k 0.9× 332 0.4× 281 0.4× 380 0.6× 342 0.8× 11 2.2k
Guy A. Howard United States 35 2.6k 2.1× 574 0.7× 452 0.7× 906 1.4× 543 1.3× 91 4.9k
John L. Fowlkes United States 38 1.8k 1.5× 651 0.8× 1.5k 2.1× 724 1.1× 549 1.3× 89 4.1k
H H Malluche United States 15 1.5k 1.2× 1.7k 2.0× 323 0.5× 1.2k 1.9× 562 1.4× 25 3.8k
Mark S. Nanes United States 35 2.4k 1.9× 1.0k 1.2× 309 0.5× 1.1k 1.7× 462 1.1× 79 4.4k
U. Trechsel Switzerland 28 723 0.6× 558 0.7× 223 0.3× 893 1.4× 216 0.5× 62 2.0k
Sutada Lotinun United States 32 2.2k 1.8× 849 1.0× 233 0.3× 993 1.5× 346 0.9× 70 3.8k

Countries citing papers authored by J. E. Wergedal

Since Specialization
Citations

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

Fields of papers citing papers by J. E. Wergedal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. E. Wergedal. 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 J. E. Wergedal. The network helps show where J. E. Wergedal may publish in the future.

Co-authorship network of co-authors of J. E. Wergedal

This figure shows the co-authorship network connecting the top 25 collaborators of J. E. Wergedal. A scholar is included among the top collaborators of J. E. Wergedal 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 J. E. Wergedal. J. E. Wergedal 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.
Mohan, Subburaman, et al.. (2007). Chemical mutagenesis induced two high bone density mouse mutants map to a concordant distal chromosome 4 locus. Bone. 41(5). 860–868. 4 indexed citations
3.
Yu, Hongrun, Subburaman Mohan, Godfred Masinde, et al.. (2007). Detecting Novel Bone Density and Bone Size Quantitative Trait Loci Using a Cross of MRL/MpJ and CAST/EiJ Inbred Mice. Calcified Tissue International. 80(2). 103–110. 14 indexed citations
4.
Srivastava, Apurva K., Subburaman Mohan, J. E. Wergedal, & David J. Baylink. (2003). A genomewide screening of N-ethyl-N-nitrosourea-mutagenized mice for musculoskeletal phenotypes☆. Bone. 33(2). 179–191. 11 indexed citations
6.
7.
Masinde, Godfred, et al.. (2002). Quantitative Trait Loci for Bone Density in Mice: The Genes Determining Total Skeletal Density and Femur Density Show Little Overlap in F2 Mice. Calcified Tissue International. 71(5). 421–428. 62 indexed citations
8.
Sheng, Matilda H.‐C., David J. Baylink, Wesley G. Beamer, et al.. (2002). Regulation of bone volume is different in the metaphyses of the femur and vertebra of C3H/HeJ and C57BL/6J mice. Bone. 30(3). 486–491. 38 indexed citations
9.
Wergedal, J. E., Matilda H.‐C. Sheng, Cheryl L. Ackert‐Bicknell, Wesley G. Beamer, & David J. Baylink. (2002). Mouse genetic model for bone strength and size phenotypes: NZB/B1NJ and RF/J inbred strains. Bone. 31(6). 670–674. 16 indexed citations
11.
Kodama, Yuji, Naohisa Miyakoshi, Thomas A. Linkhart, et al.. (2000). Effects of dietary calcium depletion and repletion on dynamic determinants of tibial bone volume in two inbred strains of mice. Bone. 27(3). 445–452. 12 indexed citations
12.
Srivastava, Apurva K., Samit Bhattacharyya, Gladys Castillo, et al.. (2000). Development and Application of a Serum C-Telopeptide and Osteocalcin Assay to Measure Bone Turnover in an Ovariectomized Rat Model. Calcified Tissue International. 66(6). 435–442. 23 indexed citations
13.
Srivastava, Apurva K., Gladys Castillo, J. E. Wergedal, Subburaman Mohan, & David J. Baylink. (2000). Development and Application of a Synthetic Peptide-Based Osteocalcin Assay for the Measurement of Bone Formation in Mouse Serum. Calcified Tissue International. 67(3). 255–259. 14 indexed citations
14.
Sheng, Matilda H.‐C., David J. Baylink, Wesley G. Beamer, et al.. (1999). Histomorphometric studies show that bone formation and bone mineral apposition rates are greater in C3H/HeJ (high-density) than C57BL/6J (low-density) mice during growth. Bone. 25(4). 421–429. 99 indexed citations
15.
Lau, K.‐H. William, et al.. (1996). Mitogenic action of hydrochlorothiazide on human osteoblasts In vitro: Requirement for platelet-derived growth factor. Calcified Tissue International. 59(6). 505–510. 5 indexed citations
16.
Resch, Alexandra, Barbara Schneider, P. Bernecker, et al.. (1995). Risk of vertebral fractures in men: relationship to mineral density of the vertebral body.. American Journal of Roentgenology. 164(6). 1447–1450. 31 indexed citations
17.
Lundy, Mark W., M. Stauffer, J. E. Wergedal, et al.. (1995). Histomorphometric analysis of iliac crest bone biopsies in placebo-treated versus fluoride-treated subjects. Osteoporosis International. 5(2). 115–129. 49 indexed citations
18.
Ohta, Takayuki, et al.. (1995). Phenytoin and fluoride act in concert to stimulate bone formation and to increase bone volume in adult male rats. Calcified Tissue International. 56(5). 390–397. 21 indexed citations
19.
Knutsen, Raymond, J. E. Wergedal, T. Kuber Sampath, David J. Baylink, & Sneha Mohan. (1993). Osteogenic Protein-1 Stimulates Proliferation and Differentiation of Human Bone Cells in Vitro. Biochemical and Biophysical Research Communications. 194(3). 1352–1358. 65 indexed citations
20.
Farley, Sally M., J. E. Wergedal, Jonathan Farley, et al.. (1992). Spinal fractures during fluoride therapy for osteoporosis: Relationship to spinal bone density. Osteoporosis International. 2(5). 213–218. 30 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026