Kasey R. Hutt

5.6k citations
17 papers · 3.0k indexed · 1 hit paper · h-index 12
  • Neurology top 1%
    • Amyotrophic Lateral Sclerosis Research 3
    • Neurological diseases and metabolism 2
  • Genetics top 2%
    • Chronic Lymphocytic Leukemia Research 2
  • Aging top 5%
    • RNA Research and Splicing 8
    • Genomics and Chromatin Dynamics 6
    • RNA modifications and cancer 3
    • RNA and protein synthesis mechanisms 3
    • CRISPR and Genetic Engineering 2

Kasey R. Hutt

17 papers receiving 3.0k citations

Hit Papers

Long pre-mRNA depletion and RNA missplicing contribute to...9592011202620162021250500750

Peers

Kasey R. Hutt
Comparison fields: 5 of 90
  • Neurology 834
  • Genetics 549
  • Aging 63
  • Molecular Biology 2.4k
  • Cancer Research 484
Replace Geoffrey G. Hicks with:
Geoffrey G. Hicks Canada
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John E. Landers United States
Andrea D’Ambrogio Italy
Vania Gelmetti Italy
Marco Baralle Italy
Kasey R. Hutt relative to Geoffrey G. Hicks Canada Geoffrey G. Hicks's profile →
Citations per field
00.5×4.2×
Geoffrey G. Hicks · 1×
Citations per year

Countries citing papers authored by Kasey R. Hutt

Since Specialization
Citations

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

Fields of papers citing papers by Kasey R. Hutt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kasey R. Hutt. 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 Kasey R. Hutt. The network helps show where Kasey R. Hutt may publish in the future.

Co-authorship network

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

All Works

17 of 17 papers shown
#Work
1 202211
2 20215
3 20212
4 20202
5 201860
6 20158
7 20141
8 201334
9 2012216
10 2012128
11
Long pre-mRNA depletion and RNA missplicing contribute to neuronal vulnerability from loss of TDP-43breakdown →
2011959
12 2010243
13 2009436
14 2008231
15 2007101
16 2007367
17 2007212

About Kasey R. Hutt

Kasey R. Hutt is a scholar working on Genetics, Neurology, Molecular Biology, Neurology and Hematology, having authored 17 papers that have together received 3.0k indexed citations. Recurring topics across this work include RNA Research and Splicing (8 papers), Genomics and Chromatin Dynamics (6 papers), RNA modifications and cancer (3 papers), RNA and protein synthesis mechanisms (3 papers), Amyotrophic Lateral Sclerosis Research (3 papers), Neurological diseases and metabolism (2 papers), CRISPR and Genetic Engineering (2 papers) and Chronic Lymphocytic Leukemia Research (2 papers). The work is most often cited by research in Neurology (834 citations), Genetics (549 citations), Aging (63 citations), Molecular Biology (2.4k citations) and Cancer Research (484 citations). Kasey R. Hutt has collaborated with scholars based in United States, Singapore and Spain. Frequent co-authors include G Yeo, Christopher K. Glass, Michael G. Rosenfeld, Tiffany Y Liang, Kenneth A. Ohgi, David W. Rose, Bong‐Gun Ju, C. Frank Bennett, Magdalini Polymenidou and Don W. Cleveland. Their work appears in journals such as PLoS Genetics, Cell, Proceedings of the National Academy of Sciences, Blood and Nature Methods.

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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