Thomas J. Vidmar

1.4k total citations
37 papers, 1.0k citations indexed

About

Thomas J. Vidmar is a scholar working on Molecular Biology, Statistics and Probability and Oncology. According to data from OpenAlex, Thomas J. Vidmar has authored 37 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Statistics and Probability and 7 papers in Oncology. Recurrent topics in Thomas J. Vidmar's work include Drug Transport and Resistance Mechanisms (6 papers), Optimal Experimental Design Methods (6 papers) and Statistical Methods in Clinical Trials (5 papers). Thomas J. Vidmar is often cited by papers focused on Drug Transport and Resistance Mechanisms (6 papers), Optimal Experimental Design Methods (6 papers) and Statistical Methods in Clinical Trials (5 papers). Thomas J. Vidmar collaborates with scholars based in United States, Germany and Canada. Thomas J. Vidmar's co-authors include Philip S. Burton, David P. Thompson, Clay T. Cramer, Norman F.H. Ho, Benny Amore, Jay T. Goodwin, Ronald T. Borchardt, Joseph W. McKean, Karen F. Wilkinson and Mary J. Ruwart and has published in prestigious journals such as PLoS ONE, Hepatology and Biometrics.

In The Last Decade

Thomas J. Vidmar

36 papers receiving 980 citations

Peers

Thomas J. Vidmar
Harold E. Selick United States
Jonathan Cheong United States
Serge Léger Canada
Bianca M. Liederer United States
Matthew Wright United States
Per Garberg Sweden
Viera Lukáčová United States
William R. Porter United States
Lucia Lazorova Sweden
Lanyan Fang United States
Harold E. Selick United States
Thomas J. Vidmar
Citations per year, relative to Thomas J. Vidmar Thomas J. Vidmar (= 1×) peers Harold E. Selick

Countries citing papers authored by Thomas J. Vidmar

Since Specialization
Citations

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

Fields of papers citing papers by Thomas J. Vidmar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas J. Vidmar

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas J. Vidmar. A scholar is included among the top collaborators of Thomas J. 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 Thomas J. Vidmar. Thomas J. 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.
Maurissen, Jacques P.J. & Thomas J. Vidmar. (2016). Repeated-measure analyses: Which one? A survey of statistical models and recommendations for reporting. Neurotoxicology and Teratology. 59. 78–84. 19 indexed citations
2.
Edwards, Terri G., Thomas J. Vidmar, Kevin J. Koeller, James K. Bashkin, & Chris Fisher. (2013). DNA Damage Repair Genes Controlling Human Papillomavirus (HPV) Episome Levels under Conditions of Stability and Extreme Instability. PLoS ONE. 8(10). e75406–e75406. 48 indexed citations
3.
Alhadeff, Jack A., et al.. (2012). Development and validation of novel enzyme activity methods to assess inhibition of matrix metalloproteinases (MMPs) in human serum by antibodies against enzyme therapeutics. Journal of Pharmaceutical and Biomedical Analysis. 70. 408–414. 4 indexed citations
4.
Crimin, Kimberly, Joseph W. McKean, & Thomas J. Vidmar. (2012). Rank‐based estimate of four‐parameter logistic model. Pharmaceutical Statistics. 11(3). 214–221. 4 indexed citations
5.
Geary, Timothy G., et al.. (2003). Biophysical characterization of a large conductance anion channel in hypodermal membranes of the gastrointestinal nematode, Ascaris suum. Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 134(4). 805–818. 4 indexed citations
6.
Burton, Philip S., Jay T. Goodwin, Thomas J. Vidmar, & Benny Amore. (2002). Predicting Drug Absorption: How Nature Made It a Difficult Problem. Journal of Pharmacology and Experimental Therapeutics. 303(3). 889–895. 67 indexed citations
7.
McKean, Joseph W. & Thomas J. Vidmar. (1994). A Comparison of Two Rank-Based Methods for the Analysis of Linear Models. The American Statistician. 48(3). 220–229. 16 indexed citations
8.
Bell, Frank P., F. Iverson, Douglas L. Arnold, & Thomas J. Vidmar. (1994). Long-term effects of Aroclor 1254 (PCBs) on plasma lipid and carnitine concentrations in rhesus monkey. Toxicology. 89(2). 139–153. 32 indexed citations
9.
Ho, Norman F.H., Thomas J. Vidmar, Craig L. Barsuhn, et al.. (1994). Theoretical Perspectives on Anthelmintic Drug Discovery: Interplay of Transport Kinetics, Physicochemical Properties, and in Vitro Activity of Anthelmintic Drugs. Journal of Pharmaceutical Sciences. 83(7). 1052–1059. 26 indexed citations
10.
Sheehy, Ann M., Jennifer L. Hoover, Bob D. Rush, et al.. (1993). Intrapulmonary Delivery of Renin Inhibitory Peptides Results in Sustained Release Because of Saturable Transport. Pharmaceutical Research. 10(10). 1548–1551. 5 indexed citations
11.
Spilman, C.H., et al.. (1992). Spontaneous hypercholesterolemia in cynomolgus monkeys: evidence for defective low-density lipoprotein catabolism. Biochimica et Biophysica Acta (BBA) - Lipids and Lipid Metabolism. 1128(1). 26–34. 2 indexed citations
12.
Thomas, E. W., et al.. (1992). Cholesterol-lowering bile acid-binding agents: novel lipophilic polyamines. Journal of Medicinal Chemistry. 35(7). 1233–1245. 12 indexed citations
13.
14.
Blake, William L., Thomas J. Vidmar, & George W. Melchior. (1992). Effects of epidermal growth factor on apo B mRNA levels and apo B accumulation in the media of primate hepatocytes in culture. Biochemical and Biophysical Research Communications. 186(1). 199–204. 3 indexed citations
15.
Rush, Bob D., et al.. (1991). Desolvation energy: a major determinant of absorption, but not clearance, of peptides in rats.. Pharmaceutical Research. 8(12). 1477–1481. 40 indexed citations
16.
Brunden, Marshall N., Rita M. Huff, Thomas J. Vidmar, & Marcus P. Cooper. (1990). Planning the purification process of active cDNA in expression cloning strategies. Journal of Theoretical Biology. 144(2). 145–154. 1 indexed citations
17.
Melchior, George W., Christine K. Castle, Thomas J. Vidmar, H. Greg Polites, & Keith R. Marotti. (1990). Apo A-I metabolism in cynomolgus monkeys: Male-female differences. Biochimica et Biophysica Acta (BBA) - Lipids and Lipid Metabolism. 1043(1). 97–105. 17 indexed citations
18.
Ruwart, Mary J., Karen F. Wilkinson, Bob D. Rush, et al.. (1989). The Integrated Value of Serum Procollagen Iii Peptide Over Time Predicts Hepatic Hydroxyproline Content and Stainable Collagen in A Model of Dietary Cirrhosis in the Rat. Hepatology. 10(5). 801–806. 87 indexed citations
19.
Thompson, David P., et al.. (1989). The Madin Darby Canine Kidney (MDCK) Epithelial Cell Monolayer as a Model Cellular Transport Barrier. Pharmaceutical Research. 6(1). 71–77. 141 indexed citations
20.
Cramer, Clay T., et al.. (1989). Neutrophil-Mediated Transport of Liposomes Across the Madin Darby Canine Kidney Epithelial Cell Monolayer. Pharmaceutical Research. 6(1). 78–84. 9 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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