Danielle Brown

21 papers receiving 484 citations

Peers

Danielle Brown
Comparison fields: 5 of 106
  • Dermatology 126
  • Pharmaceutical Science 42
  • Biochemistry 26
  • Complementary and alternative medicine 33
  • Immunology and Allergy 22
Replace Richard G. Fiscella with:
Richard G. Fiscella United States
Rajani Katta United States
Caroline Owen United Kingdom
Zhenwei Yu China
Sunghan Yim United States
Anna Julia Pietrobon Brazil
Arturo Talavera Cuba
Jonathan Batchelor United Kingdom
Julie Harper United States
Mohammad Mahdi Parvizi Iran
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Citations per year

Countries citing papers authored by Danielle Brown

Since Specialization
Citations

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

Fields of papers citing papers by Danielle Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Danielle Brown, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Danielle Brown Line = papers co-authored together Danielle Brown links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017212
2 201246
3 202037
4 201534
5 201730
6 202021
7 201920
8 201719
9 201514
10 202014
11 202010
12 202010
13 201210
14 20058
15 20178
16 20217
17
In situ activation of mouse lung macrophages by coadministration of liposomes containing the lipopeptide CGP 31362 and interleukin 2 involves interaction with T lymphocytes and natural killer cells.
19917
18 20222
19 20181
20 20171

About Danielle Brown

Danielle Brown is a scholar working on Epidemiology, Infectious Diseases, Dermatology, Neurology and Immunology, having authored 21 papers that have together received 512 indexed citations. Recurring topics across this work include Vitamin D Research Studies (2 papers), Vitamin C and Antioxidants Research (2 papers), Traumatic Brain Injury Research (2 papers), Dermatological diseases and infestations (2 papers), Traumatic Brain Injury and Neurovascular Disturbances (2 papers), Child Nutrition and Feeding Issues (1 paper), Nerve injury and regeneration (1 paper) and Allergic Rhinitis and Sensitization (1 paper). The work is most often cited by research in Dermatology (126 citations), Pharmaceutical Science (42 citations), Biochemistry (26 citations), Complementary and alternative medicine (33 citations) and Immunology and Allergy (22 citations). Danielle Brown has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Esther E. Freeman, Divya Seth, Rajani Katta, Janet Schloss, Amie Steel, P. David Adelson, Christopher P. Deibert, Michael J. Bell, Matthew Leach and Igor Dvorchik. Their work appears in journals such as Journal of the American Academy of Dermatology, Pediatric Dermatology, Child s Nervous System, The Journal of Pediatrics and Mini-Reviews in Medicinal Chemistry.

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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