Stephen Tonna

2.0k citations
18 papers · 1.3k · h-index 13

Impact in

Papers in

    • Bone Metabolism and Diseases 4
    • Amyloidosis: Diagnosis, Treatment, Outcomes 4
    • Renal Diseases and Glomerulopathies 9
    • Chronic Kidney Disease and Diabetes 3

Stephen Tonna

17 papers receiving 1.3k citations

Peers

Stephen Tonna
Comparison fields: 5 of 91
  • Nephrology 549
  • Immunology and Allergy 186
  • Genetics 114
  • Molecular Biology 540
  • Gastroenterology 30
Replace Friedhelm Hildebrandt with:
Friedhelm Hildebrandt United States
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Hiroshi Kaito Japan
Eckhard Schulze-Lohoff Germany
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Bryce G. Johnson United States
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Stephen Tonna relative to Friedhelm Hildebrandt United States Friedhelm Hildebrandt's profile →
Citations per field
00.5×1.7×
Friedhelm Hildebrandt · 1×
Citations per year

Countries citing papers authored by Stephen Tonna

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Tonna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stephen Tonna, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stephen Tonna Line = papers co-authored together Stephen Tonna links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2009319
2 2003168
3 2011163
4 2010126
5 2010114
6 201283
7 201471
8 200453
9 200838
10 200836
11 201631
12 200727
13 201325
14 20057
15 20077
16 20075
17 20223
18
EphrinB2 reverse signaling in osteoblasts is required for normal bone material strength and increased bone formation in response to parathyroid hormone (PTH)
20131

About Stephen Tonna

Stephen Tonna is a scholar working on Molecular Biology, Nephrology, Cellular and Molecular Neuroscience, Endocrinology, Diabetes and Metabolism and Immunology and Allergy, having authored 18 papers that have together received 1.3k indexed citations. Recurring topics across this work include Renal Diseases and Glomerulopathies (9 papers), Axon Guidance and Neuronal Signaling (5 papers), Bone Metabolism and Diseases (4 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (4 papers), Chronic Kidney Disease and Diabetes (3 papers), Cell Adhesion Molecules Research (3 papers), Vasculitis and related conditions (2 papers) and Growth Hormone and Insulin-like Growth Factors (2 papers). The work is most often cited by research in Nephrology (549 citations), Immunology and Allergy (186 citations), Genetics (114 citations), Molecular Biology (540 citations) and Gastroenterology (30 citations). Stephen Tonna has collaborated with scholars based in Australia, United States and China. Frequent co-authors include Martin R. Pollak, Judy Savige, Yan Yan Wang, Kesha Rana, Assam El‐Osta, Johannes Schlöndorff, Henry N. Higgs, Daniel Becker, Elizabeth Brown and Hiroyasu Tsukaguchi. Their work appears in journals such as Pediatric Nephrology, Kidney International, Journal of Bone and Mineral Research, Calcified Tissue International and Gene.

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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