Devin Brown

520 citations
12 papers · 395 · h-index 9

Impact in

Papers in

    • Virus-based gene therapy research 8
    • Hemoglobinopathies and Related Disorders 2
    • CRISPR and Genetic Engineering 3
    • Pluripotent Stem Cells Research 1

Devin Brown

12 papers receiving 383 citations

Peers

Devin Brown
Comparison fields: 5 of 60
  • Genetics 60
  • Genetics 142
  • Business and International Management 10
  • Aging 7
  • Cognitive Neuroscience 68
Replace Sivaprakash Ramalingam with:
Sivaprakash Ramalingam India
Chan-Jung Chang United States
Saumya Kumar United Kingdom
Devlin Shea United States
E Hoogendoorn Netherlands
Laura Spector United States
Xun Li China
George N. Llewellyn United States
Youngmee Sul United States
Kelcee A. Everette United States
Devin Brown relative to Sivaprakash Ramalingam India Sivaprakash Ramalingam's profile →
Citations per field
00.5×10×13.6×
Sivaprakash Ramalingam · 1×
Citations per year

Countries citing papers authored by Devin Brown

Since Specialization
Citations

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

Fields of papers citing papers by Devin Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Devin 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 Devin Brown Line = papers co-authored together Devin Brown links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 201987
2 196685
3 201869
4 201936
5 201730
6 201827
7 198823
8 202212
9 202011
10 20157
11 20245
12 20243

About Devin Brown

Devin Brown is a scholar working on Genetics, Molecular Biology, Infectious Diseases, Genetics and Oncology, having authored 12 papers that have together received 395 indexed citations. Recurring topics across this work include Virus-based gene therapy research (8 papers), Parvovirus B19 Infection Studies (3 papers), CRISPR and Genetic Engineering (3 papers), Hemoglobinopathies and Related Disorders (2 papers), Plant and Fungal Interactions Research (1 paper), Pluripotent Stem Cells Research (1 paper), Mosquito-borne diseases and control (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Genetics (60 citations), Genetics (142 citations), Business and International Management (10 citations), Aging (7 citations) and Cognitive Neuroscience (68 citations). Devin Brown has collaborated with scholars based in United States, Italy and Japan. Frequent co-authors include Roger P. Hollis, Donald B. Kohn, D.O. Walter, W. R. Adey, J. Rhodes, Katelyn E. Masiuk, Anastasia Lomova, Beatriz Campo-Fernández, Zulema Romero and Xiaoyan Wang. Their work appears in journals such as Molecular Therapy, Molecular Therapy — Methods & Clinical Development, Human Gene Therapy, Stem Cells and Blood.

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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