Kevin Drenner

3.0k citations
12 papers · 931 · 1 hit paper · h-index 9

Impact in

  • Neurology top 2%
    • Amyotrophic Lateral Sclerosis Research
    • Parkinson's Disease Mechanisms and Treatments
    • Neuroinflammation and Neurodegeneration Mechanisms
  • Genetics top 2%
    • Neurogenetic and Muscular Disorders Research

Papers in

    • Cancer-related gene regulation 2
    • RNA Research and Splicing 2
    • Amyotrophic Lateral Sclerosis Research 5

Kevin Drenner

11 papers receiving 923 citations

Kevin Drenner's Hit Papers

Premature polyadenylation-mediated loss of stathmin-2 is a hallmark of TDP-43-dependent neurodegeneration 2019 · 368 citations
3680+2+4Years since publication100200300

Peers

Kevin Drenner
Comparison fields: 5 of 62
  • Neurology 545
  • Genetics 332
  • Neurology 100
  • Cellular and Molecular Neuroscience 141
  • Molecular Biology 512
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Kevin Drenner relative to Seiya Tokunaga United States Seiya Tokunaga's profile →
Citations per field
00.5×3.8×
Seiya Tokunaga · 1×
Citations per year

Countries citing papers authored by Kevin Drenner

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Drenner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1
Premature polyadenylation-mediated loss of stathmin-2 is a hallmark of TDP-43-dependent neurodegeneration
Hit paper breakdown →
2019368
2 2015153
3 2017151
4 201781
5 202063
6 201755
7 201932
8 201814
9 202111
10 20212
11 20211
12 20200

About Kevin Drenner

Kevin Drenner is a scholar working on Molecular Biology, Neurology, Genetics, Cancer Research and Oncology, having authored 12 papers that have together received 931 indexed citations. Recurring topics across this work include Amyotrophic Lateral Sclerosis Research (5 papers), Neurogenetic and Muscular Disorders Research (4 papers), Cancer Genomics and Diagnostics (3 papers), Cancer-related gene regulation (2 papers), RNA Research and Splicing (2 papers), Cancer Mechanisms and Therapy (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Alzheimer's disease research and treatments (1 paper). The work is most often cited by research in Neurology (545 citations), Genetics (332 citations), Neurology (100 citations), Cellular and Molecular Neuroscience (141 citations) and Molecular Biology (512 citations). Kevin Drenner has collaborated with scholars based in United States, Germany and Singapore. Frequent co-authors include Don W. Cleveland, Clotilde Lagier‐Tourenne, Ying Sun, Shuying Sun, John Ravits, Sandrine Da Cruz, Moira A. McMahon, Frank Rigo, Ouyang Zhang and Maria José Gómez-Rodríguez. Their work appears in journals such as Acta Neuropathologica, PLoS ONE, Clinical Cancer Research, Journal of Pharmacology and Experimental Therapeutics and Oncotarget.

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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