Matthew Fell

47 papers receiving 1.9k citations

Matthew Fell's Hit Papers

Phosphoproteomics reveals that Parkinson's disease kinase LRRK2 regulates a subset of Rab GTPases 2016 · 722 citations
7220+3+6Years since publication200400600

Peers

Matthew Fell
Comparison fields: 5 of 118
  • Neurology 793
  • Cellular and Molecular Neuroscience 485
  • Cell Biology 390
  • Biological Psychiatry 48
  • Neurology 147
Replace Silvia Cerri with:
Silvia Cerri Italy
Éva M. Szegő Germany
Selma Kanazir Serbia
Iddo Magen Israel
Amy L. Wilson‐Delfosse United States
Ayşe Ulusoy Germany
Annika Vaarmann Estonia
Jyothisri Kondapalli United States
Mikiei Tanaka United States
Kengo Uemura Japan
Matthew Fell relative to Silvia Cerri Italy Silvia Cerri's profile →
Citations per field
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Silvia Cerri · 1×
Citations per year

Countries citing papers authored by Matthew Fell

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Fell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Phosphoproteomics reveals that Parkinson's disease kinase LRRK2 regulates a subset of Rab GTPases
Hit paper breakdown →
2016722
2 2015213
3 2008160
4 2017113
5 201175
6 201861
7 200453
8 202052
9 200752
10 202244
11 202034
12 200531
13 200931
14 202129
15 200928
16 202127
17 202321
18 200521
19 201517
20 201315

About Matthew Fell

Matthew Fell is a scholar working on Genetics, Molecular Biology, Surgery, Neurology and Cellular and Molecular Neuroscience, having authored 56 papers that have together received 2.0k indexed citations. Recurring topics across this work include Cleft Lip and Palate Research (20 papers), Parkinson's Disease Mechanisms and Treatments (9 papers), Craniofacial Disorders and Treatments (8 papers), Receptor Mechanisms and Signaling (6 papers), Neuroscience and Neuropharmacology Research (4 papers), Cellular transport and secretion (3 papers), Mast cells and histamine (3 papers) and Cardiac, Anesthesia and Surgical Outcomes (2 papers). The work is most often cited by research in Neurology (793 citations), Cellular and Molecular Neuroscience (485 citations), Cell Biology (390 citations), Biological Psychiatry (48 citations) and Neurology (147 citations). Matthew Fell has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Kjell Svensson, J. Michael Ellis, John A. Morrow, Bryan G. Johnson, Brian Fiske, Genta Ito, Stefanie Wachter, Marco A. S. Baptista, Paul Davies and Martin Steger. Their work appears in journals such as The Cleft Palate-Craniofacial Journal, Journal of Plastic Reconstructive & Aesthetic Surgery, Journal of Pharmacology and Experimental Therapeutics, Neuropharmacology and International Journal of Oral and Maxillofacial Surgery.

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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