Thomas D. Mueller

7.9k citations
102 papers · 4.9k · h-index 38

Impact in

Papers in

    • TGF-β signaling in diseases 31
    • Bone Metabolism and Diseases 12
    • Ubiquitin and proteasome pathways 8
    • Connective Tissue Growth Factor Research 7
    • Peptidase Inhibition and Analysis 7

Thomas D. Mueller

101 papers receiving 4.8k citations

Peers

Thomas D. Mueller
Comparison fields: 5 of 132
  • Molecular Biology 2.9k
  • Immunology and Allergy 206
  • Rheumatology 459
  • Oncology 687
  • Cell Biology 386
Replace Gabriela G. Loots with:
Gabriela G. Loots United States
Yoichi Kato Japan
Ken–ichi Yamamura Japan
Marina Schorpp‐Kistner Germany
Bernard Perbal France
Glenn Longenecker United States
Gareth J. Inman United Kingdom
Ramón Merino Spain
Bent Brachvogel Germany
Ronald Kriz United States
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Citations per field
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Gabriela G. Loots · 1×
Citations per year

Countries citing papers authored by Thomas D. Mueller

Since Specialization
Citations

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

Fields of papers citing papers by Thomas D. Mueller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas D. Mueller. 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 Thomas D. Mueller. The network helps show where Thomas D. Mueller may publish in the future.

Co-authors

The 25 scholars most cited alongside Thomas D. Mueller, 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 Thomas D. Mueller Line = papers co-authored together Thomas D. Mueller links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 102 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016266
2 2012236
3 2004184
4 2015178
5 2012155
6 2002154
7 2017154
8 2002146
9 2010146
10 2007134
11 2007130
12 2005128
13 2015122
14 2004118
15 2016117
16 2009107
17 2000106
18 2019103
19 2008101
20 200398

About Thomas D. Mueller

Thomas D. Mueller is a scholar working on Molecular Biology, Oncology, Genetics, Immunology and Allergy and Rheumatology, having authored 102 papers that have together received 4.9k indexed citations. Recurring topics across this work include TGF-β signaling in diseases (31 papers), Bone Metabolism and Diseases (12 papers), Cell Adhesion Molecules Research (11 papers), Connective tissue disorders research (8 papers), Monoclonal and Polyclonal Antibodies Research (8 papers), Ubiquitin and proteasome pathways (8 papers), Connective Tissue Growth Factor Research (7 papers) and Peptidase Inhibition and Analysis (7 papers). The work is most often cited by research in Molecular Biology (2.9k citations), Immunology and Allergy (206 citations), Rheumatology (459 citations), Oncology (687 citations) and Cell Biology (386 citations). Thomas D. Mueller has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Joachim Nickel, Walter Sebald, Juli Feigon, Jinli Zhang, Alexander Kotzsch, Timothy A. Springer, Andrew P. Hinck, Peter ten Dijke, Petra Knaus and David Yadin. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE, Molecular Pharmacology, Journal of Molecular Biology and The Journal of Clinical Endocrinology & Metabolism.

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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