Kevin A. Burns

2.6k citations
23 papers · 1.2k indexed · h-index 16

Kevin A. Burns

22 papers receiving 1.1k citations

Peers

Kevin A. Burns
Comparison fields: 5 of 97
  • Developmental Neuroscience 319
  • Neurology 113
  • Cellular and Molecular Neuroscience 238
  • Cell Biology 188
  • Molecular Biology 696
Replace Zachary B. Gaber with:
Zachary B. Gaber United States
Jennie Close United States
Giuseppe Lupo Italy
Jason E. Long United States
T. Ian Simpson United Kingdom
Denise Stenzel Germany
Nina Offenhäuser Italy
Alessandro Sessa Italy
Daichi Kawaguchi Japan
Tomomi Shimogori Japan
Kevin A. Burns relative to Zachary B. Gaber United States Zachary B. Gaber's profile →
Citations per field
00.5×1.6×
Zachary B. Gaber · 1×
Citations per year

Countries citing papers authored by Kevin A. Burns

Since Specialization
Citations

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

Fields of papers citing papers by Kevin A. Burns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin A. Burns. 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 Kevin A. Burns. The network helps show where Kevin A. Burns may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 201958
3 201820
4 20171
5 2017137
6 201535
7 2014101
8 201328
9 20129
10 201252
11 201014
12 20101
13 200857
14 200831
15 200854
16 200792
17 200772
18 200568
19 2004229
20
Journal selection decisions: a biomedical library operations research model. I. The framework.
19763

About Kevin A. Burns

Kevin A. Burns is a scholar working on Developmental Neuroscience, Medical Laboratory Technology and Genetics, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (6 papers), Genomics and Phylogenetic Studies (6 papers), Neurogenesis and neuroplasticity mechanisms (6 papers), Glioma Diagnosis and Treatment (4 papers), Bioinformatics and Genomic Networks (4 papers), Neonatal and fetal brain pathology (2 papers), Genomics and Rare Diseases (2 papers) and Pluripotent Stem Cells Research (2 papers). The work is most often cited by research in Developmental Neuroscience (319 citations), Neurology (113 citations) and Cellular and Molecular Neuroscience (238 citations). Kevin A. Burns has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Chia‐Yi Kuan, Peter D. Vize, Christina James‐Zorn, Aaron M. Zorn, Joshua D. Fortriede, Virgilio Ponferrada, Kamran Karimi, Pasko Rakić, Chia-Yi Kuan and Aryn Schloemer. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Neuroscience.

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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