Daniel Mona

1.2k total citations · 1 hit paper
6 papers, 707 citations indexed

About

Daniel Mona is a scholar working on Neurology, Physiology and Organic Chemistry. According to data from OpenAlex, Daniel Mona has authored 6 papers receiving a total of 707 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Neurology, 2 papers in Physiology and 1 paper in Organic Chemistry. Recurrent topics in Daniel Mona's work include Parkinson's Disease Mechanisms and Treatments (4 papers), Botulinum Toxin and Related Neurological Disorders (3 papers) and Neurological disorders and treatments (2 papers). Daniel Mona is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (4 papers), Botulinum Toxin and Related Neurological Disorders (3 papers) and Neurological disorders and treatments (2 papers). Daniel Mona collaborates with scholars based in Switzerland, United States and Netherlands. Daniel Mona's co-authors include Markus Britschgi, Roland Riek, Nicholas M. I. Taylor, Philippe Ringler, Henning Stahlberg, Matthias E. Lauer, Ricardo Guerrero-Ferreira, Pratibha Kumari, Ana‐Andreea Arteni and Joeri Verasdonck and has published in prestigious journals such as Nature Communications, eLife and Advances in experimental medicine and biology.

In The Last Decade

Daniel Mona

6 papers receiving 703 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Cryo-EM structure of alpha-synuclein fibrils

2018 441 citations Ricardo Guerrero-Ferreira, Nicholas M. I. Taylor et al. eLife profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniel Mona Switzerland	5	430	425	283	101	83	6	707
Pratibha Kumari Switzerland	7	333 0.8×	283 0.7×	232 0.8×	86 0.9×	59 0.7×	7	565
Nikolai Lorenzen Denmark	11	342 0.8×	361 0.8×	245 0.9×	86 0.9×	49 0.6×	11	676
Youqi Tao China	14	285 0.7×	282 0.7×	304 1.1×	78 0.8×	54 0.7×	25	671
Shahin Zibaee United Kingdom	8	353 0.8×	272 0.6×	237 0.8×	120 1.2×	82 1.0×	9	590
Gudrun Heim Germany	8	391 0.9×	374 0.9×	546 1.9×	112 1.1×	53 0.6×	8	1.0k
Woo Shik Shin United States	5	305 0.7×	319 0.8×	200 0.7×	63 0.6×	48 0.6×	13	526
Lise Giehm Denmark	12	420 1.0×	477 1.1×	547 1.9×	128 1.3×	54 0.7×	17	1.0k
Amberley D. Stephens United Kingdom	15	526 1.2×	378 0.9×	356 1.3×	220 2.2×	52 0.6×	23	957
Hamed Shaykhalishahi Germany	13	235 0.5×	338 0.8×	258 0.9×	71 0.7×	20 0.2×	19	556

Countries citing papers authored by Daniel Mona

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Mona

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Mona

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Mona. A scholar is included among the top collaborators of Daniel Mona based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Mona. Daniel Mona is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Brevé, John J. P., Walter Boiten, Bram van der Gaag, et al.. (2025). Synaptic enrichment of pSer129 alpha-synuclein correlates with dopaminergic denervation in early-stage Parkinson’s disease. Nature Communications. 16(1). 6630–6630. 2 indexed citations

2.

Moors, Tim E., Daniel Mona, Gonzalo Durán-Pacheco, et al.. (2022). Multi-platform quantitation of alpha-synuclein human brain proteoforms suggests disease-specific biochemical profiles of synucleinopathies. Acta Neuropathologica Communications. 10(1). 82–82. 8 indexed citations

3.

Guerrero-Ferreira, Ricardo, Nicholas M. I. Taylor, Ana‐Andreea Arteni, et al.. (2019). Two new polymorphic structures of human full-length alpha-synuclein fibrils solved by cryo-electron microscopy. eLife. 8. 222 indexed citations

4.

Guerrero-Ferreira, Ricardo, Nicholas M. I. Taylor, Daniel Mona, et al.. (2018). Cryo-EM structure of alpha-synuclein fibrils. eLife. 7. 441 indexed citations breakdown →

5.

Morgenthaler, Martin, Johannes D. Aebi, Fiona Grüninger, et al.. (2008). A fluorine scan of non-peptidic inhibitors of neprilysin: Fluorophobic and fluorophilic regions in an enzyme active site. Journal of Fluorine Chemistry. 129(9). 852–865. 19 indexed citations

6.

Moon, Richard P., Daniel Bur, Hansruedi Loetscher, et al.. (1998). Studies on Plasmepsins I and II from the Malarial Parasite Plasmodium falciparum and their Exploitation as Drug Targets. Advances in experimental medicine and biology. 436. 397–406. 15 indexed citations

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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