Michele Trucksis

2.5k total citations
37 papers, 1.6k citations indexed

About

Michele Trucksis is a scholar working on Infectious Diseases, Molecular Biology and Epidemiology. According to data from OpenAlex, Michele Trucksis has authored 37 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Infectious Diseases, 19 papers in Molecular Biology and 16 papers in Epidemiology. Recurrent topics in Michele Trucksis's work include Mycobacterium research and diagnosis (12 papers), Antibiotic Resistance in Bacteria (7 papers) and Clostridium difficile and Clostridium perfringens research (7 papers). Michele Trucksis is often cited by papers focused on Mycobacterium research and diagnosis (12 papers), Antibiotic Resistance in Bacteria (7 papers) and Clostridium difficile and Clostridium perfringens research (7 papers). Michele Trucksis collaborates with scholars based in United States, United Kingdom and Chile. Michele Trucksis's co-authors include David C. Hooper, E Y Ng, Adel M. Talaat, James B. Kaper, Renate Reimschuessel, Alessio Fasano, Richard E. Depew, Joel Michalski, James E. Galen and Jane M. Michalski and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Gastroenterology and Cancer Research.

In The Last Decade

Michele Trucksis

37 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michele Trucksis United States 18 573 539 419 389 389 37 1.6k
Christelle M. Roux United States 23 881 1.5× 514 1.0× 206 0.5× 204 0.5× 140 0.4× 28 1.7k
Awdhesh Kalia United States 23 878 1.5× 920 1.7× 459 1.1× 611 1.6× 153 0.4× 43 2.6k
Michael C. Chao United States 21 811 1.4× 549 1.0× 368 0.9× 501 1.3× 311 0.8× 32 1.7k
James E. Bina United States 25 744 1.3× 260 0.5× 816 1.9× 145 0.4× 493 1.3× 48 2.0k
Christopher T. D. Price United States 25 974 1.7× 248 0.5× 1.1k 2.6× 275 0.7× 174 0.4× 50 2.0k
Dachuan Lin China 21 501 0.9× 313 0.6× 350 0.8× 159 0.4× 717 1.8× 35 1.5k
Olga Danilchanka United States 17 820 1.4× 851 1.6× 161 0.4× 622 1.6× 352 0.9× 17 1.8k
Sylvie Goussard France 24 771 1.3× 214 0.4× 440 1.1× 189 0.5× 945 2.4× 35 1.8k
Jacqueline T. Balthazar United States 21 298 0.5× 276 0.5× 116 0.3× 327 0.8× 472 1.2× 30 1.5k
Gunnar N. Schroeder United Kingdom 20 605 1.1× 316 0.6× 956 2.3× 120 0.3× 158 0.4× 34 1.5k

Countries citing papers authored by Michele Trucksis

Since Specialization
Citations

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

Fields of papers citing papers by Michele Trucksis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Trucksis

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Trucksis. A scholar is included among the top collaborators of Michele Trucksis 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 Michele Trucksis. Michele Trucksis 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
2.
Henn, Matthew R., Christopher B. Ford, Edward R. O’Brien, et al.. (2018). 621. Treatment of Recurrent Clostridium difficile Infection with SER-109 Increases the Concentration of Secondary Bile Acids in a Dose-Dependent Manner. Open Forum Infectious Diseases. 5(suppl_1). S226–S227. 1 indexed citations
5.
Ford, Christopher B., Matthew R. Henn, Jessica A. Bryant, et al.. (2018). 1641. Treatment of Recurrent Clostridium difficile Infection With SER-109 Reduces Gastrointestinal Carriage of Antimicrobial Resistance Genes. Open Forum Infectious Diseases. 5(suppl_1). S46–S47. 1 indexed citations
6.
Stroh, Mark, Punam Sandhu, Jacqueline B. McCrea, et al.. (2014). Lack of meaningful effect of ridaforolimus on the pharmacokinetics of midazolam in cancer patients: Model prediction and clinical confirmation. The Journal of Clinical Pharmacology. 54(11). 1256–1262. 4 indexed citations
7.
Stroh, Mark, Xiaodong Li, Deborah Panebianco, et al.. (2012). The minimal impact of food on the pharmacokinetics of ridaforolimus. Cancer Chemotherapy and Pharmacology. 70(1). 177–182. 4 indexed citations
8.
Stroh, Mark, John Palcza, Jacqueline B. McCrea, et al.. (2012). The effect of multiple doses of rifampin and ketoconazole on the single-dose pharmacokinetics of ridaforolimus. Cancer Chemotherapy and Pharmacology. 69(5). 1247–1253. 5 indexed citations
9.
Trucksis, Michele, Evan Friedman, Adekemi Taylor, et al.. (2009). Abstract #3604: A phase I single-rising dose study evaluating the safety, tolerability, pharmacokinetics and pharmacodynamics of an oral akt inhibitor in healthy male volunteers. Cancer Research. 69. 3604–3604. 4 indexed citations
10.
Pagán-Ramos, Eileen, Sharon Master, Christopher L. Pritchett, et al.. (2006). Molecular and Physiological Effects of Mycobacterial oxyR Inactivation. Journal of Bacteriology. 188(7). 2674–2680. 27 indexed citations
11.
Ansede, John H., et al.. (2004). Identification ofMycobacterium marinumvirulence genes using signature-tagged mutagenesis and the goldfish model of mycobacterial pathogenesis. FEMS Microbiology Letters. 232(1). 75–81. 35 indexed citations
12.
Reimschuessel, Renate, et al.. (2002). Goldfish as an animal model system for mycobacterial infection. Methods in enzymology on CD-ROM/Methods in enzymology. 358. 29–39. 12 indexed citations
13.
Talaat, Adel M. & Michele Trucksis. (2000). Transformation and transposition of the genome of Mycobacterium marinum. American Journal of Veterinary Research. 61(2). 125–128. 19 indexed citations
14.
Trucksis, Michele, et al.. (1999). Superoxide production in phagocytes obtained from Mycobacterium marinum-stimulated goldfish (Carassius auratus) that were exposed to copper. American Journal of Veterinary Research. 60(6). 669–675. 1 indexed citations
15.
Talaat, Adel M., Michele Trucksis, Andrew S. Kane, & Renate Reimschuessel. (1999). Pathogenicity of Mycobacterium fortuitum and Mycobacterium smegmatis to goldfish, Carassius auratus. Veterinary Microbiology. 66(2). 151–164. 52 indexed citations
16.
Talaat, Adel M., Renate Reimschuessel, & Michele Trucksis. (1997). Identification of mycobacteria infecting fish to the species level using polymerase chain reaction and restriction enzyme analysis. Veterinary Microbiology. 58(2-4). 229–237. 96 indexed citations
18.
Moriuchi, Hiroyuki & Michele Trucksis. (1996). Urinary Tract Infection Caused by Hafnia alvei. Infectious Diseases in Clinical Practice. 5(8). 517–517. 1 indexed citations
19.
Ng, E Y, Michele Trucksis, & David C. Hooper. (1994). Quinolone resistance mediated by norA: physiologic characterization and relationship to flqB, a quinolone resistance locus on the Staphylococcus aureus chromosome. Antimicrobial Agents and Chemotherapy. 38(6). 1345–1355. 187 indexed citations
20.
Trucksis, Michele, et al.. (1991). Bronchiectasis: a current view.. PubMed. 11. 170–205. 10 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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