Matthew R. Geringer

909 total citations
16 papers, 711 citations indexed

About

Matthew R. Geringer is a scholar working on Rehabilitation, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Matthew R. Geringer has authored 16 papers receiving a total of 711 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Rehabilitation, 8 papers in Molecular Biology and 3 papers in Infectious Diseases. Recurrent topics in Matthew R. Geringer's work include Wound Healing and Treatments (11 papers), Bacterial biofilms and quorum sensing (8 papers) and Antimicrobial Resistance in Staphylococcus (3 papers). Matthew R. Geringer is often cited by papers focused on Wound Healing and Treatments (11 papers), Bacterial biofilms and quorum sensing (8 papers) and Antimicrobial Resistance in Staphylococcus (3 papers). Matthew R. Geringer collaborates with scholars based in United States, China and Philippines. Matthew R. Geringer's co-authors include Robert D. Galiano, Thomas A. Mustoe, Seok Jong Hong, Akhil K. Seth, Kai P. Leung, Anandev N. Gurjala, Khang T. Nguyen, Mark S. Smeltzer, Sonya Agnew and Ping Xie and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Plastic & Reconstructive Surgery.

In The Last Decade

Matthew R. Geringer

15 papers receiving 668 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew R. Geringer United States 13 385 378 110 106 85 16 711
Joel Gil United States 13 443 1.2× 390 1.0× 100 0.9× 95 0.9× 109 1.3× 26 917
José Alberto Bertot Valdés United States 11 337 0.9× 314 0.8× 91 0.8× 84 0.8× 45 0.5× 30 740
Priscilla L. Phillips United States 12 384 1.0× 404 1.1× 95 0.9× 139 1.3× 101 1.2× 19 831
Samuel J. Hooper United Kingdom 11 203 0.5× 351 0.9× 80 0.7× 86 0.8× 55 0.6× 12 1.0k
Hannah Trøstrup Denmark 15 220 0.6× 359 0.9× 105 1.0× 34 0.3× 87 1.0× 34 685
Qingping Yang United States 16 526 1.4× 554 1.5× 132 1.2× 230 2.2× 141 1.7× 38 1.2k
João João Mendes Portugal 10 206 0.5× 171 0.5× 126 1.1× 32 0.3× 195 2.3× 27 629
Jake Everett United States 9 166 0.4× 587 1.6× 128 1.2× 38 0.4× 39 0.5× 15 890
C. Davies United Kingdom 9 356 0.9× 207 0.5× 41 0.4× 44 0.4× 183 2.2× 17 601
Anne‐Marie Salisbury United Kingdom 13 138 0.4× 142 0.4× 48 0.4× 78 0.7× 40 0.5× 26 436

Countries citing papers authored by Matthew R. Geringer

Since Specialization
Citations

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

Fields of papers citing papers by Matthew R. Geringer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew R. Geringer. 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 Matthew R. Geringer. The network helps show where Matthew R. Geringer may publish in the future.

Co-authorship network of co-authors of Matthew R. Geringer

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew R. Geringer. A scholar is included among the top collaborators of Matthew R. Geringer 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 Matthew R. Geringer. Matthew R. Geringer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Geringer, Matthew R., Laveta Stewart, Faraz Shaikh, et al.. (2024). Epidemiology and timing of infectious complications from battlefield-related burn injuries. Burns. 50(9). 107200–107200. 2 indexed citations
2.
Geringer, Matthew R., et al.. (2022). Interrater agreement of the HEART score history component: A chart review study. SHILAP Revista de lepidopterología. 3(3). e12732–e12732. 4 indexed citations
3.
McGann, Patrick, Matthew R. Geringer, François Lebreton, et al.. (2021). Pan-drug resistant Providencia rettgeri contributing to a fatal case of COVID-19. Journal of Medical Microbiology. 70(8). 14 indexed citations
4.
Geringer, Matthew R., et al.. (2020). Proton Pump Inhibitor-Induced Hypomagnesemia: A Rare, Potentially Fatal Complication. Cureus. 12(5). e8191–e8191.
5.
Park, Eugene, Akhil K. Seth, Matthew R. Geringer, et al.. (2015). The use of desiccation to treat Staphylococcus aureus biofilm‐infected wounds. Wound Repair and Regeneration. 24(2). 394–401. 14 indexed citations
6.
Leung, Kai P., Peter D’Arpa, Akhil K. Seth, et al.. (2014). Dermal wound transcriptomic responses to Infection with Pseudomonas aeruginosa versus Klebsiella pneumoniae in a rabbit ear wound model. BMC Clinical Pathology. 14(1). 20–20. 15 indexed citations
7.
Seth, Akhil K., Matthew R. Geringer, Khang T. Nguyen, et al.. (2013). Bacteriophage Therapy for Staphylococcus aureus Biofilm–Infected Wounds. Plastic & Reconstructive Surgery. 131(2). 225–234. 89 indexed citations
8.
Nguyen, Khang T., Akhil K. Seth, Seok Jong Hong, et al.. (2013). Deficient cytokine expression and neutrophil oxidative burst contribute to impaired cutaneous wound healing in diabetic, biofilm‐containing chronic wounds. Wound Repair and Regeneration. 21(6). 833–841. 69 indexed citations
9.
Seth, Akhil K., Khang T. Nguyen, Matthew R. Geringer, et al.. (2013). Noncontact, low‐frequency ultrasound as an effective therapy against Pseudomonas aeruginosa–infected biofilm wounds. Wound Repair and Regeneration. 21(2). 266–274. 40 indexed citations
10.
Seth, Akhil K., Matthew R. Geringer, Seok Jong Hong, et al.. (2012). Comparative Analysis of Single-Species and Polybacterial Wound Biofilms Using a Quantitative, In Vivo, Rabbit Ear Model. PLoS ONE. 7(8). e42897–e42897. 68 indexed citations
11.
Seth, Akhil K., Matthew R. Geringer, Seok Jong Hong, et al.. (2012). In vivo modeling of biofilm-infected wounds: A review. Journal of Surgical Research. 178(1). 330–338. 82 indexed citations
12.
Seth, Akhil K., Matthew R. Geringer, Robert D. Galiano, et al.. (2012). Quantitative Comparison and Analysis of Species-Specific Wound Biofilm Virulence Using an In Vivo, Rabbit-Ear Model. Journal of the American College of Surgeons. 215(3). 388–399. 52 indexed citations
13.
Seth, Akhil K., Matthew R. Geringer, Anandev N. Gurjala, et al.. (2012). Treatment of Pseudomonas aeruginosa Biofilm–Infected Wounds with Clinical Wound Care Strategies. Plastic & Reconstructive Surgery. 129(2). 262e–274e. 63 indexed citations
14.
Seth, Akhil K., Matthew R. Geringer, Anandev N. Gurjala, et al.. (2012). Understanding the host inflammatory response to wound infection: An in vivo study of Klebsiella pneumoniae in a rabbit ear wound model. Wound Repair and Regeneration. 20(2). 214–225. 23 indexed citations
15.
Buck, Donald W., et al.. (2011). The TallyHo Polygenic Mouse Model of Diabetes. Plastic & Reconstructive Surgery. 128(5). 427e–437e. 26 indexed citations
16.
Gurjala, Anandev N., Matthew R. Geringer, Akhil K. Seth, et al.. (2011). Development of a novel, highly quantitative in vivo model for the study of biofilm‐impaired cutaneous wound healing. Wound Repair and Regeneration. 19(3). 400–410. 150 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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