Marilyn J. Dillon

1.4k total citations · 1 hit paper
7 papers, 1.1k citations indexed

About

Marilyn J. Dillon is a scholar working on Immunology, Food Science and Neurology. According to data from OpenAlex, Marilyn J. Dillon has authored 7 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Immunology, 4 papers in Food Science and 3 papers in Neurology. Recurrent topics in Marilyn J. Dillon's work include Essential Oils and Antimicrobial Activity (3 papers), Immune Response and Inflammation (3 papers) and Listeria monocytogenes in Food Safety (3 papers). Marilyn J. Dillon is often cited by papers focused on Essential Oils and Antimicrobial Activity (3 papers), Immune Response and Inflammation (3 papers) and Listeria monocytogenes in Food Safety (3 papers). Marilyn J. Dillon collaborates with scholars based in United States, Netherlands and Germany. Marilyn J. Dillon's co-authors include Douglas A. Drevets, Pieter J. M. Leenen, Cord Sunderkötter, Nico van Rooijen, Tatjana Nikolić, Martin Stehling, Jan Ehrchen, Julie A. Stoner, Daniel J. Brackett and Michael S. Bronze and has published in prestigious journals such as The Journal of Immunology, The Journal of Infectious Diseases and Applied Microbiology and Biotechnology.

In The Last Decade

Marilyn J. Dillon

7 papers receiving 1.1k 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.

Subpopulations of Mouse Blood Monocytes Differ in Maturation Stage and Inflammatory Response

2004 890 citations Cord Sunderkötter, Tatjana Nikolić et al. The Journal of Immunology profile →

Peers

Marilyn J. Dillon

IMMUN

MB

NEURO

ONCOL

EPIDE

Xiongwen Wu China

Beatrix Schumak Germany

Marion Salou France

Inmaculada Gayoso Spain

Matthew M. Meredith United States

Ludmila N. Drutskaya Russia

Paramita Baruah United Kingdom

Giuseppina Colonna Romano Italy

Johnny Bonnardel France

I Bernard France

Xiongwen Wu China

Marilyn J. Dillon

466 ×0.6

IMMUN

236 ×1.4

MB

97 ×0.6

NEURO

149 ×1.0

ONCOL

149 ×1.1

EPIDE

Citations per year, relative to Marilyn J. Dillon Marilyn J. Dillon (= 1×) peers Xiongwen Wu

Countries citing papers authored by Marilyn J. Dillon

Since Specialization

Citations

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

Fields of papers citing papers by Marilyn J. Dillon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marilyn J. Dillon

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

All Works

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7 of 7 papers shown

1.

Hocker, James R., Douglas A. Drevets, Marilyn J. Dillon, & Jay S. Hanas. (2012). Discriminating experimental Listeria monocytogenes infections in mice using serum profiling. Applied Microbiology and Biotechnology. 96(4). 1049–1058. 1 indexed citations

2.

Drevets, Douglas A., et al.. (2010). IFN-γ triggers CCR2-independent monocyte entry into the brain during systemic infection by virulent Listeria monocytogenes. Brain Behavior and Immunity. 24(6). 919–929. 26 indexed citations

3.

Zee, Marten van der, Willem A. Dik, Yolanda S. Kap, et al.. (2010). Synthetic Human Chorionic Gonadotropin–Related Oligopeptides Impair Early Innate Immune Responses toListeria monocytogenesin Mice. The Journal of Infectious Diseases. 201(7). 1072–1080. 16 indexed citations

4.

Drevets, Douglas A., et al.. (2010). Severe Listeria monocytogenes Infection Induces Development of Monocytes with Distinct Phenotypic and Functional Features. The Journal of Immunology. 185(4). 2432–2441. 24 indexed citations

5.

Drevets, Douglas A., et al.. (2008). Innate Responses to Systemic Infection by Intracellular Bacteria Trigger Recruitment of Ly-6Chigh Monocytes to the Brain. The Journal of Immunology. 181(1). 529–536. 22 indexed citations

6.

Sunderkötter, Cord, Tatjana Nikolić, Marilyn J. Dillon, et al.. (2004). Subpopulations of Mouse Blood Monocytes Differ in Maturation Stage and Inflammatory Response. The Journal of Immunology. 172(7). 4410–4417. 890 indexed citations breakdown →

7.

Drevets, Douglas A., Marilyn J. Dillon, Nico van Rooijen, et al.. (2004). The Ly-6Chigh Monocyte Subpopulation Transports Listeria monocytogenes into the Brain during Systemic Infection of Mice. The Journal of Immunology. 172(7). 4418–4424. 115 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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