Mark L. Johnson

5.9k total citations · 1 hit paper
96 papers, 4.6k citations indexed

About

Mark L. Johnson is a scholar working on Molecular Biology, Orthopedics and Sports Medicine and Oncology. According to data from OpenAlex, Mark L. Johnson has authored 96 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Molecular Biology, 20 papers in Orthopedics and Sports Medicine and 16 papers in Oncology. Recurrent topics in Mark L. Johnson's work include Bone Metabolism and Diseases (21 papers), Bone health and osteoporosis research (20 papers) and Wnt/β-catenin signaling in development and cancer (17 papers). Mark L. Johnson is often cited by papers focused on Bone Metabolism and Diseases (21 papers), Bone health and osteoporosis research (20 papers) and Wnt/β-catenin signaling in development and cancer (17 papers). Mark L. Johnson collaborates with scholars based in United States, United Kingdom and Canada. Mark L. Johnson's co-authors include Lynda F. Bonewald, Lindsay M. Faunt, Mohamed A. Kamel, Nuria Lara-Castillo, Merle A. Sande, Nalini M. Rajamannan, G. Gong, Robert R. Recker, Linda L. Humphrey and Steven M. Teutsch and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Annals of Internal Medicine and PLoS ONE.

In The Last Decade

Mark L. Johnson

92 papers receiving 4.5k citations

Hit Papers

Osteocytes, mechanosensing and Wnt signaling 2008 2026 2014 2020 2008 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark L. Johnson United States 34 2.4k 1.3k 844 767 537 96 4.6k
Yūji Shimizu Japan 29 3.8k 1.6× 408 0.3× 612 0.7× 1.4k 1.9× 556 1.0× 238 7.0k
Xiaofeng Li China 41 4.5k 1.9× 452 0.4× 543 0.6× 1.1k 1.4× 286 0.5× 330 7.8k
David A. Conner United States 37 4.3k 1.8× 375 0.3× 720 0.9× 507 0.7× 368 0.7× 88 6.9k
Brad Bolon United States 46 4.4k 1.8× 343 0.3× 843 1.0× 1.3k 1.8× 1.1k 2.1× 227 9.0k
Airong Qian China 38 2.6k 1.1× 543 0.4× 367 0.4× 534 0.7× 850 1.6× 178 5.1k
Inna Chervoneva United States 38 1.3k 0.5× 462 0.4× 513 0.6× 997 1.3× 121 0.2× 142 5.2k
Yan Zhang China 44 4.4k 1.8× 290 0.2× 291 0.3× 553 0.7× 470 0.9× 301 7.1k
Peter A. Friedman United States 51 4.4k 1.8× 198 0.2× 490 0.6× 806 1.1× 653 1.2× 203 8.4k
Scott C. Henderson United States 34 2.1k 0.9× 181 0.1× 529 0.6× 515 0.7× 461 0.9× 93 4.8k
Akira Sasaki Japan 49 3.2k 1.3× 569 0.4× 553 0.7× 3.4k 4.4× 707 1.3× 529 10.5k

Countries citing papers authored by Mark L. Johnson

Since Specialization
Citations

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

Fields of papers citing papers by Mark L. Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark L. Johnson. 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 Mark L. Johnson. The network helps show where Mark L. Johnson may publish in the future.

Co-authorship network of co-authors of Mark L. Johnson

This figure shows the co-authorship network connecting the top 25 collaborators of Mark L. Johnson. A scholar is included among the top collaborators of Mark L. Johnson 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 Mark L. Johnson. Mark L. Johnson 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.
Lara-Castillo, Nuria, Leticia Brotto, Michael Wacker, et al.. (2023). Muscle secreted factors enhance activation of the PI3K/Akt and β-catenin pathways in murine osteocytes. Bone. 174. 116833–116833. 5 indexed citations
2.
Taylor, Erik A., Eve Donnelly, Xiaomei Yao, et al.. (2019). Sequential Treatment of Estrogen Deficient, Osteopenic Rats with Alendronate, Parathyroid Hormone (1–34), or Raloxifene Alters Cortical Bone Mineral and Matrix Composition. Calcified Tissue International. 106(3). 303–314. 13 indexed citations
3.
Maurel, D, Tsutomu Matsumoto, Julian Vallejo, et al.. (2019). Characterization of a novel murine Sost ERT2 Cre model targeting osteocytes. PMC. 2 indexed citations
4.
Maurel, D, Tsutomu Matsumoto, Julian Vallejo, et al.. (2019). Characterization of a novel murine Sost ERT2 Cre model targeting osteocytes. Bone Research. 7(1). 6–6. 22 indexed citations
5.
Begonia, Mark T., Mark Dallas, Mark L. Johnson, & Ganesh Thiagarajan. (2017). Comparison of strain measurement in the mouse forearm using subject-specific finite element models, strain gaging, and digital image correlation. Biomechanics and Modeling in Mechanobiology. 16(4). 1243–1253. 15 indexed citations
6.
Ross, Ryan D., Alvin S. Acerbo, Jonathan Almer, et al.. (2016). HBM Mice Have Altered Bone Matrix Composition and Improved Material Toughness. Calcified Tissue International. 99(4). 384–395. 5 indexed citations
7.
Karasik, David, Fernando Rivadeneira, & Mark L. Johnson. (2016). The genetics of bone mass and susceptibility to bone diseases. Nature Reviews Rheumatology. 12(6). 323–334. 70 indexed citations
8.
Lara-Castillo, Nuria, Mohamed A. Kamel, Behzâd Javaheri, et al.. (2015). In vivo mechanical loading rapidly activates β-catenin signaling in osteocytes through a prostaglandin mediated mechanism. Bone. 76. 58–66. 106 indexed citations
9.
Brotto, Marco & Mark L. Johnson. (2014). Endocrine Crosstalk Between Muscle and Bone. Current Osteoporosis Reports. 12(2). 135–141. 81 indexed citations
10.
Xiao, Zhousheng, Cao Li, Jinsong Huang, et al.. (2014). Osteoblast-Specific Deletion of Pkd2 Leads to Low-Turnover Osteopenia and Reduced Bone Marrow Adiposity. PLoS ONE. 9(12). e114198–e114198. 33 indexed citations
11.
Johnson, Mark L.. (2012). LRP5 and bone mass regulation: Where are we now?. BoneKEy Reports. 1. 1–1. 34 indexed citations
12.
Bourbeau, Jean & Mark L. Johnson. (2009). New and Controversial Therapies for Chronic Obstructive Pulmonary Disease. Proceedings of the American Thoracic Society. 6(6). 553–554. 12 indexed citations
13.
Akhter, M. P., Daniel Wells, Diane M. Cullen, et al.. (2004). Bone biomechanical properties in LRP5 mutant mice. Bone. 35(1). 162–169. 120 indexed citations
14.
Rendell, Marc, et al.. (2002). Skin Blood Flow Response in the Rat Model of Wound Healing: Expression of Vasoactive Factors. Journal of Surgical Research. 107(1). 18–26. 24 indexed citations
15.
Johnson, Mark L., et al.. (2001). THE ROLES OF iNOS IN LIVER ISCHEMIA-REPERFUSION INJURY. Shock. 16(5). 355–360. 91 indexed citations
16.
Johnson, Mark L., et al.. (1997). Linkage of a Gene Causing High Bone Mass to Human Chromosome 11 (11q12-13). The American Journal of Human Genetics. 60(6). 1326–1332. 238 indexed citations
17.
Barger-Lux, M. Janet, Robert P. Heaney, James M. Hayes, et al.. (1995). Vitamin D receptor gene polymorphism, bone mass, body size, and vitamin D receptor density. Calcified Tissue International. 57(2). 161–162. 103 indexed citations
18.
Johnson, Mark L. & Lindsay M. Faunt. (1992). [1] Parameter estimation by least-squares methods. Methods in enzymology on CD-ROM/Methods in enzymology. 210. 1–37. 284 indexed citations
20.
Horiuchi, Ryuya, et al.. (1982). Affinity labeling of the plasma membrane 3,3',5-triiodo-L-thyronine receptor in GH3 cells.. Proceedings of the National Academy of Sciences. 79(18). 5527–5531. 54 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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