Jay Hayes

1.9k total citations · 1 hit paper
13 papers, 1.4k citations indexed

About

Jay Hayes is a scholar working on Microbiology, Epidemiology and Molecular Biology. According to data from OpenAlex, Jay Hayes has authored 13 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Microbiology, 7 papers in Epidemiology and 5 papers in Molecular Biology. Recurrent topics in Jay Hayes's work include Bacterial Infections and Vaccines (7 papers), Pneumonia and Respiratory Infections (6 papers) and Streptococcal Infections and Treatments (3 papers). Jay Hayes is often cited by papers focused on Bacterial Infections and Vaccines (7 papers), Pneumonia and Respiratory Infections (6 papers) and Streptococcal Infections and Treatments (3 papers). Jay Hayes collaborates with scholars based in United States, Italy and Germany. Jay Hayes's co-authors include Garth D. Ehrlich, Fen Hu, J. Christopher Post, Bethany Dice, Michael L. Forbes, Paul Stoodley, David P. Greenberg, Laura Nistico, Joseph E. Kerschner and Armin Gieseke and has published in prestigious journals such as JAMA, PLoS ONE and Journal of Bacteriology.

In The Last Decade

Jay Hayes

13 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Direct Detection of Bacterial Biofilms on the Middle-Ear Mucosa of Children With Chronic Otitis Media

2006 676 citations Luanne Hall‐Stoodley, Fen Hu et al. JAMA profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jay Hayes United States	10	523	510	495	327	243	13	1.4k
Bethany Dice United States	8	399 0.8×	397 0.8×	363 0.7×	277 0.8×	211 0.9×	8	1.1k
W. Edward Swords United States	19	486 0.9×	463 0.9×	309 0.6×	181 0.6×	213 0.9×	41	1.3k
Wenzhou Hong United States	19	530 1.0×	386 0.8×	530 1.1×	282 0.9×	284 1.2×	36	1.4k
Eric R. Lafontaine United States	21	1.0k 2.0×	417 0.8×	405 0.8×	48 0.1×	186 0.8×	48	1.7k
Leen Van Simaey Belgium	21	542 1.0×	416 0.8×	591 1.2×	22 0.1×	185 0.8×	29	1.2k
Vlademir Vicente Cantarelli Brazil	19	239 0.5×	197 0.4×	77 0.2×	55 0.2×	65 0.3×	59	1.0k
Simo Räisänen Norway	18	201 0.4×	62 0.1×	122 0.2×	166 0.5×	151 0.6×	72	820
Randy Keefe United States	6	262 0.5×	242 0.5×	204 0.4×	20 0.1×	29 0.1×	7	586
Paula Kriz Czechia	24	1.2k 2.3×	346 0.7×	1.3k 2.6×	22 0.1×	30 0.1×	46	2.0k
Amanda Drilling Australia	17	113 0.2×	220 0.4×	252 0.5×	244 0.7×	65 0.3×	26	796

Countries citing papers authored by Jay Hayes

Since Specialization

Citations

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

Fields of papers citing papers by Jay Hayes

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jay Hayes

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

Boissy, Robert, Azad Ahmed, Benjamin Janto, et al.. (2011). Comparative supragenomic analyses among the pathogens Staphylococcus aureus, Streptococcus pneumoniae, and Haemophilus influenzae Using a modification of the finite supragenome model. BMC Genomics. 12(1). 187–187. 42 indexed citations

Kerschner, Joseph E., Géza Erdös, Fen Hu, et al.. (2010). Partial Characterization of Normal and Haemophilus Influenzae—Infected Mucosal Complementary DNA Libraries in Chinchilla Middle Ear Mucosa. Annals of Otology Rhinology & Laryngology. 119(4). 270–278. 2 indexed citations

Forbes, Michael L., Edward Horsey, N. Luisa Hiller, et al.. (2008). Strain-Specific Virulence Phenotypes of Streptococcus pneumoniae Assessed Using the Chinchilla laniger Model of Otitis Media. PLoS ONE. 3(4). e1969–e1969. 34 indexed citations

Buchinsky, Farrel J., Michael L. Forbes, Jay Hayes, et al.. (2007). Virulence phenotypes of low-passage clinical isolates of Nontypeable Haemophilus influenzae assessed using the chinchilla laniger model of otitis media. BMC Microbiology. 7(1). 56–56. 19 indexed citations

Hiller, N. Luisa, Benjamin Janto, Justin Hogg, et al.. (2007). Comparative Genomic Analyses of Seventeen Streptococcus pneumoniae Strains: Insights into the Pneumococcal Supragenome. Journal of Bacteriology. 189(22). 8186–8195. 218 indexed citations

Hogg, Justin, Fen Hu, Benjamin Janto, et al.. (2007). Characterization and modeling of the Haemophilus influenzae core and supragenomes based on the complete genomic sequences of Rd and 12 clinical nontypeable strains. Genome biology. 8(6). R103–R103. 175 indexed citations

Hall‐Stoodley, Luanne, Fen Hu, Armin Gieseke, et al.. (2006). Direct Detection of Bacterial Biofilms on the Middle-Ear Mucosa of Children With Chronic Otitis Media. JAMA. 296(2). 202–202. 676 indexed citations breakdown →

Erdös, Géza, Sameera Sayeed, Fen Hu, et al.. (2006). Construction and characterization of a highly redundant Pseudomonas aeruginosa genomic library prepared from 12 clinical isolates: Application to studies of gene distribution among populations. International Journal of Pediatric Otorhinolaryngology. 70(11). 1891–1900. 5 indexed citations

Dohar, Joseph E., Patricia A. Hebda, Richard Veeh, et al.. (2005). Mucosal Biofilm Formation on Middle‐Ear Mucosa in a Nonhuman Primate Model of Chronic Suppurative Otitis Media. The Laryngoscope. 115(8). 1469–1472. 80 indexed citations

10.

Shen, Kai, Bethany Dice, Benjamin Janto, et al.. (2005). Characterization, Distribution, and Expression of Novel Genes among Eight Clinical Isolates of Streptococcuspneumoniae. Infection and Immunity. 74(1). 321–330. 42 indexed citations

11.

Shen, Kai, Sameera Sayeed, Azad Ahmed, et al.. (2005). Identification, Distribution, and Expression of Novel Genes in 10 Clinical Isolates of Nontypeable Haemophilus influenzae. Infection and Immunity. 73(6). 3479–3491. 50 indexed citations

12.

Erdös, Géza, Sameera Sayeed, Fen Hu, et al.. (2003). Development and characterization of a pooled Haemophilus influenzae genomic library for the evaluation of gene expression changes associated with mucosal biofilm formation in otitis media. International Journal of Pediatric Otorhinolaryngology. 67(7). 749–755. 12 indexed citations

13.

Hayes, Jay, et al.. (1971). THE GEOLOGICAL AND STRUCTURAL FRAMEWORK OF THE OFFSHORE KIMBERLEY BLOCK (BROWSE BASIN) AREA, WESTERN AUSTRALIA. The APEA Journal. 11(1). 64–70. 7 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.

Explore authors with similar magnitude of impact