Brian M. M. Ahmer

5.3k total citations
71 papers, 3.9k citations indexed

About

Brian M. M. Ahmer is a scholar working on Molecular Biology, Food Science and Genetics. According to data from OpenAlex, Brian M. M. Ahmer has authored 71 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 37 papers in Food Science and 25 papers in Genetics. Recurrent topics in Brian M. M. Ahmer's work include Salmonella and Campylobacter epidemiology (29 papers), Bacterial Genetics and Biotechnology (23 papers) and Vibrio bacteria research studies (20 papers). Brian M. M. Ahmer is often cited by papers focused on Salmonella and Campylobacter epidemiology (29 papers), Bacterial Genetics and Biotechnology (23 papers) and Vibrio bacteria research studies (20 papers). Brian M. M. Ahmer collaborates with scholars based in United States, Egypt and United Kingdom. Brian M. M. Ahmer's co-authors include Fred Heffron, Jenée N. Smith, R. Goodier, Max Teplitski, Tony Romeo, Anice Sabag-Daigle, Eric W. Triplett, Yuemei Dong, A. Leonardo Iniguez and Anastasia H. Potts and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Immunology and PLoS ONE.

In The Last Decade

Brian M. M. Ahmer

67 papers receiving 3.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian M. M. Ahmer United States 34 2.2k 1.3k 1.2k 1.2k 600 71 3.9k
Fernando C. Soncini Argentina 29 1.5k 0.7× 1.4k 1.1× 1.3k 1.1× 1.3k 1.1× 520 0.9× 55 4.1k
Sof’ya N. Senchenkova Russia 34 1.8k 0.8× 608 0.5× 732 0.6× 1.5k 1.2× 1.1k 1.8× 234 4.2k
Andrew J. Roe United Kingdom 37 1.3k 0.6× 582 0.5× 844 0.7× 1.6k 1.3× 429 0.7× 93 3.4k
Kenneth E. Sanderson Canada 36 1.9k 0.9× 1.4k 1.1× 1.1k 0.9× 923 0.7× 1.2k 2.0× 78 3.6k
Tobias A. Oelschlaeger Germany 33 1.6k 0.7× 1.1k 0.9× 544 0.4× 933 0.8× 384 0.6× 61 3.6k
Gabriella Pessi Switzerland 34 2.6k 1.2× 541 0.4× 1.1k 0.9× 562 0.5× 662 1.1× 66 4.6k
Stephen J. Libby United States 42 2.1k 0.9× 2.3k 1.8× 1.7k 1.4× 2.0k 1.6× 1.2k 1.9× 68 5.8k
Eleonora Garcı́a Véscovi Argentina 24 1.1k 0.5× 712 0.6× 960 0.8× 843 0.7× 345 0.6× 49 2.5k
Eckhard Strauch Germany 30 1.3k 0.6× 413 0.3× 626 0.5× 1.1k 0.9× 744 1.2× 80 2.8k
Glenn M. Young United States 28 1.1k 0.5× 527 0.4× 987 0.8× 680 0.5× 317 0.5× 65 2.8k

Countries citing papers authored by Brian M. M. Ahmer

Since Specialization
Citations

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

Fields of papers citing papers by Brian M. M. Ahmer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian M. M. Ahmer. 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 Brian M. M. Ahmer. The network helps show where Brian M. M. Ahmer may publish in the future.

Co-authorship network of co-authors of Brian M. M. Ahmer

This figure shows the co-authorship network connecting the top 25 collaborators of Brian M. M. Ahmer. A scholar is included among the top collaborators of Brian M. M. Ahmer 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 Brian M. M. Ahmer. Brian M. M. Ahmer 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.
Abdelhamid, Ahmed G., et al.. (2025). Sublethal shell egg processing increases virulence of Salmonella enterica serovar Enteritidis in C57BL/6 mice. Food Bioscience. 69. 106883–106883.
2.
Rego, E. Hesper, et al.. (2024). MtlD as a therapeutic target for intestinal and systemic bacterial infections. Journal of Bacteriology. 207(1). e0048024–e0048024.
3.
Rodríguez-Ramos, Josué, Michael Shaffer, Anice Sabag-Daigle, et al.. (2023). Exposing new taxonomic variation with inflammation — a murine model-specific genome database for gut microbiome researchers. Microbiome. 11(1). 114–114. 5 indexed citations
4.
Sabag-Daigle, Anice, et al.. (2022). Sugar-Phosphate Toxicities Attenuate Salmonella Fitness in the Gut. Journal of Bacteriology. 204(12). e0034422–e0034422. 9 indexed citations
5.
Sabag-Daigle, Anice, Mark J. Mitton‐Fry, Angela Di Capua, et al.. (2022). Serendipitous Discovery of a Competitive Inhibitor of FraB, a Salmonella Deglycase and Drug Target. Pathogens. 11(10). 1102–1102. 2 indexed citations
6.
Sengupta, Anindita, Justin T. Seffernick, Anice Sabag-Daigle, et al.. (2019). Integrated Use of Biochemical, Native Mass Spectrometry, Computational, and Genome-Editing Methods to Elucidate the Mechanism of a deglycase. Journal of Molecular Biology. 431(22). 4497–4513. 11 indexed citations
7.
Borton, Mikayla, Anice Sabag-Daigle, Lindsey Solden, et al.. (2017). Chemical and pathogen-induced inflammation disrupt the murine intestinal microbiome. Microbiome. 5(1). 47–47. 112 indexed citations
8.
Venturi, Vittorio, Sujatha Subramoni, Anice Sabag-Daigle, & Brian M. M. Ahmer. (2017). Methods to Study Solo/Orphan Quorum-Sensing Receptors. Methods in molecular biology. 1673. 145–159. 6 indexed citations
9.
Sabag-Daigle, Anice, Jessica L. Dyszel, Juan F. González, Mohamed Medhat Ali, & Brian M. M. Ahmer. (2015). Identification of sdiA-regulated genes in a mouse commensal strain of Enterobacter cloacae. Frontiers in Cellular and Infection Microbiology. 5. 47–47. 18 indexed citations
10.
Canals, Rocı́o, Xiao-Qin Xia, Catrina C. Fronick, et al.. (2012). High-throughput comparison of gene fitness among related bacteria. BMC Genomics. 13(1). 212–212. 20 indexed citations
11.
Smith, Jenée N., et al.. (2010). Salmonella SdiA Recognizes N-acyl Homoserine Lactone Signals from Pectobacterium carotovorum in Vitro, but Not in a Bacterial Soft Rot. Molecular Plant-Microbe Interactions. 23(3). 273–282. 34 indexed citations
12.
Dyszel, Jessica L., et al.. (2010). E. coli K-12 and EHEC Genes Regulated by SdiA. PLoS ONE. 5(1). e8946–e8946. 65 indexed citations
13.
Dyszel, Jessica L., Jenée N. Smith, Jitesh A. Soares, et al.. (2009). Salmonella enterica Serovar Typhimurium Can Detect Acyl Homoserine Lactone Production by Yersinia enterocolitica in Mice. Journal of Bacteriology. 192(1). 29–37. 80 indexed citations
14.
Ahmer, Brian M. M., et al.. (2007). Methods in Cell-to-Cell Signaling in Salmonella. Methods in molecular biology. 394. 307–322. 10 indexed citations
15.
Iniguez, A. Leonardo, et al.. (2005). Regulation of Enteric Endophytic Bacterial Colonization by Plant Defenses. Molecular Plant-Microbe Interactions. 18(2). 169–178. 214 indexed citations
16.
Goodier, R. & Brian M. M. Ahmer. (2001). SirA Orthologs Affect both Motility and Virulence. Journal of Bacteriology. 183(7). 2249–2258. 91 indexed citations
17.
Ahmer, Brian M. M.. (1999). Salmonella typhimurium recognition of intestinal environments: Response. Trends in Microbiology. 7(6). 222–223. 6 indexed citations
18.
Ahmer, Brian M. M., Jeroen van Reeuwijk, Cynthia Timmers, P J Valentine, & Fred Heffron. (1998). Salmonella typhimurium Encodes an SdiA Homolog, a Putative Quorum Sensor of the LuxR Family, That Regulates Genes on the Virulence Plasmid. Journal of Bacteriology. 180(5). 1185–1193. 201 indexed citations
19.
20.
Ahmer, Brian M. M., Michael G. Thomas, Ray A. Larsen, & Kathleen Postle. (1995). Characterization of the exbBD operon of Escherichia coli and the role of ExbB and ExbD in TonB function and stability. Journal of Bacteriology. 177(16). 4742–4747. 85 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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