Daimon P. Simmons

1.1k total citations
17 papers, 559 citations indexed

About

Daimon P. Simmons is a scholar working on Immunology, Infectious Diseases and Hematology. According to data from OpenAlex, Daimon P. Simmons has authored 17 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Immunology, 3 papers in Infectious Diseases and 3 papers in Hematology. Recurrent topics in Daimon P. Simmons's work include Immune Cell Function and Interaction (6 papers), Immune Response and Inflammation (6 papers) and Immunotherapy and Immune Responses (4 papers). Daimon P. Simmons is often cited by papers focused on Immune Cell Function and Interaction (6 papers), Immune Response and Inflammation (6 papers) and Immunotherapy and Immune Responses (4 papers). Daimon P. Simmons collaborates with scholars based in United States, Greece and Oman. Daimon P. Simmons's co-authors include Clifford V. Harding, W. Henry Boom, David H. Canaday, Lakshmi Ramachandra, Yichun Liu, William Savage, Howard Meyerson, Pamela A. Wearsch, Ying Wang and Michael B. Brenner and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Immunology and Cell Reports.

In The Last Decade

Daimon P. Simmons

16 papers receiving 545 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daimon P. Simmons United States 10 338 127 110 103 75 17 559
Meryem Aloulou France 14 569 1.7× 183 1.4× 78 0.7× 80 0.8× 71 0.9× 23 797
Fanching Lin United States 7 210 0.6× 97 0.8× 84 0.8× 80 0.8× 83 1.1× 13 462
Dirk Darnell United States 8 475 1.4× 86 0.7× 128 1.2× 125 1.2× 55 0.7× 12 607
Pamela A. Welch United States 10 297 0.9× 94 0.7× 50 0.5× 100 1.0× 84 1.1× 15 657
Carla S. R. Lankford United States 6 360 1.1× 193 1.5× 65 0.6× 72 0.7× 120 1.6× 8 631
Morgan Taillardet France 12 684 2.0× 206 1.6× 65 0.6× 171 1.7× 55 0.7× 14 1.0k
Ariel Isaacs Australia 12 325 1.0× 135 1.1× 195 1.8× 179 1.7× 133 1.8× 25 658
Femke J. M. Muller Netherlands 8 607 1.8× 162 1.3× 54 0.5× 72 0.7× 68 0.9× 12 837
Jayendra Kumar Krishnaswamy United States 14 546 1.6× 112 0.9× 54 0.5× 86 0.8× 77 1.0× 22 798
Hiroo Katsuya Japan 14 242 0.7× 148 1.2× 60 0.5× 65 0.6× 111 1.5× 57 536

Countries citing papers authored by Daimon P. Simmons

Since Specialization
Citations

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

Fields of papers citing papers by Daimon P. Simmons

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daimon P. Simmons. 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 Daimon P. Simmons. The network helps show where Daimon P. Simmons may publish in the future.

Co-authorship network of co-authors of Daimon P. Simmons

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

All Works

17 of 17 papers shown
1.
Yeung, Melissa Y., Naoka Murakami, Daimon P. Simmons, et al.. (2023). Impact of allele-specific anti–human leukocyte antigen class I antibodies on organ allocation. American Journal of Transplantation. 23(9). 1388–1400. 1 indexed citations
2.
Tolan, Nicole V., Joshua E. Lewis, Daimon P. Simmons, et al.. (2023). Lessons learned: A look back at the performance of nine COVID-19 serologic assays and their proposed utility. Clinical Biochemistry. 117. 60–68.
3.
Simmons, Daimon P., Hung Nguyen, Emma Gomez-Rivas, et al.. (2022). SLAMF7 engagement superactivates macrophages in acute and chronic inflammation. Science Immunology. 7(68). eabf2846–eabf2846. 63 indexed citations
4.
Nilles, Eric J., Elizabeth W. Karlson, Maia Norman, et al.. (2021). Evaluation of Three Commercial and Two Non-Commercial Immunoassays for the Detection of Prior Infection to SARS-CoV-2. The Journal of Applied Laboratory Medicine. 6(6). 1561–1570. 8 indexed citations
5.
Slowikowski, Kamil, Hung N. Nguyen, Erika H. Noss, et al.. (2020). CUX1 and IκBζ (NFKBIZ) mediate the synergistic inflammatory response to TNF and IL-17A in stromal fibroblasts. Proceedings of the National Academy of Sciences. 117(10). 5532–5541. 56 indexed citations
6.
Donado, Carlos, Anh Cao, Daimon P. Simmons, et al.. (2020). A Two-Cell Model for IL-1β Release Mediated by Death-Receptor Signaling. Cell Reports. 31(1). 107466–107466. 22 indexed citations
7.
Vege, Sunitha, Daimon P. Simmons, Helen Mah, et al.. (2020). Overcoming the challenges of interpreting complex and uncommon RH alleles from whole genomes. Vox Sanguinis. 115(8). 790–801. 7 indexed citations
8.
Uljon, Sacha, Daimon P. Simmons, Jason M. Baron, et al.. (2019). Validation and Implementation of an Ordering Alert to Improve the Efficiency of Monoclonal Gammopathy Evaluation. American Journal of Clinical Pathology. 153(3). 396–406. 2 indexed citations
9.
Simmons, Daimon P., et al.. (2016). Antibodies against HLA-DP recognize broadly expressed epitopes. Human Immunology. 77(12). 1128–1139. 11 indexed citations
10.
Simmons, Daimon P., et al.. (2016). Lupus anticoagulant testing using two parallel methods detects additional cases and predicts persistent positivity. Clinical Chemistry and Laboratory Medicine (CCLM). 56(8). 1289–1296. 9 indexed citations
11.
Simmons, Daimon P. & William Savage. (2015). Hemolysis from ABO Incompatibility. Hematology/Oncology Clinics of North America. 29(3). 429–443. 39 indexed citations
12.
Wearsch, Pamela A., Daimon P. Simmons, David H. Canaday, et al.. (2012). Type I IFN drives a distinctive dendritic cell maturation phenotype that allows continued MHC-II synthesis and antigen processing (106.21). The Journal of Immunology. 188(1_Supplement). 106.21–106.21. 1 indexed citations
13.
Liu, Yichun, Daimon P. Simmons, Xiaoxia Li, et al.. (2012). TLR2 Signaling Depletes IRAK1 and Inhibits Induction of Type I IFN by TLR7/9. The Journal of Immunology. 188(3). 1019–1026. 35 indexed citations
14.
Simmons, Daimon P., Pamela A. Wearsch, David H. Canaday, et al.. (2012). Type I IFN Drives a Distinctive Dendritic Cell Maturation Phenotype That Allows Continued Class II MHC Synthesis and Antigen Processing. The Journal of Immunology. 188(7). 3116–3126. 126 indexed citations
15.
Simmons, Daimon P., David H. Canaday, Yi Liu, et al.. (2010). Mycobacterium tuberculosis and TLR2 Agonists Inhibit Induction of Type I IFN and Class I MHC Antigen Cross Processing by TLR9. The Journal of Immunology. 185(4). 2405–2415. 59 indexed citations
16.
Ramachandra, Lakshmi, Daimon P. Simmons, & Clifford V. Harding. (2009). MHC molecules and microbial antigen processing in phagosomes. Current Opinion in Immunology. 21(1). 98–104. 68 indexed citations
17.
Pecora, Nicole, Scott A. Fulton, Scott M. Reba, et al.. (2008). Mycobacterium bovis BCG decreases MHC-II expression in vivo on murine lung macrophages and dendritic cells during aerosol infection. Cellular Immunology. 254(2). 94–104. 52 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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