Tom Vidmar

673 total citations
24 papers, 504 citations indexed

About

Tom Vidmar is a scholar working on Molecular Biology, Cancer Research and Pharmacology. According to data from OpenAlex, Tom Vidmar has authored 24 papers receiving a total of 504 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Cancer Research and 4 papers in Pharmacology. Recurrent topics in Tom Vidmar's work include Carcinogens and Genotoxicity Assessment (4 papers), Statistical Methods in Clinical Trials (3 papers) and Antibiotics Pharmacokinetics and Efficacy (3 papers). Tom Vidmar is often cited by papers focused on Carcinogens and Genotoxicity Assessment (4 papers), Statistical Methods in Clinical Trials (3 papers) and Antibiotics Pharmacokinetics and Efficacy (3 papers). Tom Vidmar collaborates with scholars based in United States, Russia and Canada. Tom Vidmar's co-authors include Alice H. Lin, Robert W. Murray, K.R. Marotti, Evan B. Smith, Steven L. Settle, Mark E. Schnute, T. Sunyer, Olga V. Nemirovskiy, Alison M. Bendele and Peter Ruminski and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Journal of Nutrition and Antimicrobial Agents and Chemotherapy.

In The Last Decade

Tom Vidmar

21 papers receiving 457 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Vidmar United States 11 148 141 130 88 56 24 504
Marie-Thérèse Labro France 12 88 0.6× 58 0.4× 139 1.1× 65 0.7× 27 0.5× 20 512
Richard Petrucci United States 8 228 1.5× 83 0.6× 113 0.9× 261 3.0× 76 1.4× 8 708
E van Strijen Netherlands 13 157 1.1× 75 0.5× 133 1.0× 132 1.5× 12 0.2× 17 579
Stella Z. Doktor United States 14 316 2.1× 164 1.2× 56 0.4× 89 1.0× 17 0.3× 21 665
M Tanaka Japan 13 228 1.5× 108 0.8× 200 1.5× 186 2.1× 115 2.1× 23 689
Monica Borgonovi Belgium 10 97 0.7× 169 1.2× 181 1.4× 116 1.3× 8 0.1× 19 423
P. W. Muggleton United Kingdom 13 144 1.0× 77 0.5× 186 1.4× 115 1.3× 27 0.5× 32 562
Yanhong Shang China 15 202 1.4× 90 0.6× 43 0.3× 58 0.7× 19 0.3× 43 574
K Venkatesan India 13 142 1.0× 314 2.2× 56 0.4× 88 1.0× 74 1.3× 49 588
R. J. McRipley United States 11 245 1.7× 128 0.9× 69 0.5× 65 0.7× 23 0.4× 17 712

Countries citing papers authored by Tom Vidmar

Since Specialization
Citations

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

Fields of papers citing papers by Tom Vidmar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Vidmar

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Vidmar. A scholar is included among the top collaborators of Tom Vidmar 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 Tom Vidmar. Tom Vidmar 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.
2.
Vidmar, Tom, et al.. (2016). Exudative Inflammatory Lesions in the Nasal Cavities of the 26-Week Tg.rasH2 Mice Oral Gavage Carcinogenicity Studies. International Journal of Toxicology. 36(1). 21–28.
3.
Vidmar, Tom, et al.. (2015). Regulatory Forum Opinion Piece*. Toxicologic Pathology. 44(1). 5–8. 2 indexed citations
4.
Vidmar, Tom, et al.. (2014). Regulatory Forum Opinion Piece*. Toxicologic Pathology. 43(5). 611–620. 4 indexed citations
5.
Vidmar, Tom, et al.. (2014). Trend Analysis of Body Weight Parameters, Mortality, and Incidence of Spontaneous Tumors in Tg.rasH2 Mice. International Journal of Toxicology. 33(6). 475–481. 1 indexed citations
6.
Vidmar, Tom, et al.. (2013). Relationship of Body Weight Parameters with the Incidence of Common Spontaneous Tumors in Tg.rasH2 Mice. Toxicologic Pathology. 42(7). 1143–1152. 4 indexed citations
7.
8.
Davis, John P., Renee M. Zaya, Craig L. Barsuhn, et al.. (2004). Interrelationships among physicochemical properties, absorption and anthelmintic activities of 2‐desoxoparaherquamide and selected analogs. Journal of Veterinary Pharmacology and Therapeutics. 27(3). 169–181. 10 indexed citations
9.
Goodwin, Jay T., Robert A. Conradi, Philip S. Burton, B. Mao, & Tom Vidmar. (1999). Strategies toward predicting peptide cellular permeability from computed molecular descriptors. Journal of Peptide Research. 53(4). 355–369. 28 indexed citations
10.
Olson, S.C., et al.. (1998). In vitro metabolism of ceftiofur in bovine tissues. Journal of Veterinary Pharmacology and Therapeutics. 21(2). 112–120. 15 indexed citations
11.
Chapman, D L, et al.. (1998). Quantitative Evaluation of Leukocyte Infiltration into the Spinal Cord in a Model of Experimental Autoimmune Encephalomyelitis: Statistical-Analytical Techniques for Use in Evaluating Drugs. International Journal of Immunopathology and Pharmacology. 11(3). 117–137. 4 indexed citations
12.
Hornish, Rex E., et al.. (1996). Ceftiofur hydrochloride: plasma and tissue distribution in swine following intramuscular administration at various doses. Journal of Veterinary Pharmacology and Therapeutics. 19(3). 192–199. 19 indexed citations
13.
Davison, K. L., Rex E. Hornish, Arthur L. Craigmill, et al.. (1995). [14C]Ceftiofur Sodium Absorption, Distribution, Metabolism, and Excretion in Sheep following Intramuscular Injections. Journal of Agricultural and Food Chemistry. 43(6). 1589–1597. 15 indexed citations
14.
Millérioux, L, et al.. (1995). Determination of ceftiofur and its desfuroylceftiofur-related metabolites in swine tissues by high-performance liquid chromatography. Journal of Chromatography B Biomedical Sciences and Applications. 673(2). 231–244. 42 indexed citations
15.
Martin, L. N., Kenneth F. Soike, Michael Murphey‐Corb, et al.. (1994). Effects of U-75875, a peptidomimetic inhibitor of retroviral proteases, on simian immunodeficiency virus infection in rhesus monkeys. Antimicrobial Agents and Chemotherapy. 38(6). 1277–1283. 19 indexed citations
16.
Hunt, Charles E., et al.. (1992). Dietary Polyunsaturated to Saturated Fatty Acid Ratio Alters Hepatic LDL Transport in Cynomolgus Macaques Fed Low Cholesterol Diets. Journal of Nutrition. 122(10). 1960–1970. 15 indexed citations
17.
Diani, A. R., et al.. (1987). Analysis of pancreatic islet cells and hormone content in the spontaneously diabetic KKAy mouse by morphometry, immunocytochemistry and radioimmunoassay. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 412(1). 53–61. 19 indexed citations
18.
Vidmar, Tom, et al.. (1987). The KKA<sup>y</sup> Mouse: A Model for the Rapid Development of Glomerular Capillary Basement Membrane Thickening. Journal of Vascular Research. 24(6). 297–303. 23 indexed citations
19.
20.
Vidmar, Tom & M.N. Brunden. (1980). Optimal allocation with fixed power in a completely randomized design with levels of subsampling. Communication in Statistics- Theory and Methods. 9(7). 757–763. 1 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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