Gérard Pierron

20.2k citations
100 papers · 10.9k indexed · 6 hit papers · h-index 43

Impact in

Papers in

Gérard Pierron

99 papers receiving 10.8k citations

Hit Papers

Functional Domains of NEAT1 Architectural lncRNA Induce Paraspeckle Assembly through Phase Separation 2018 · 422 citations
42220052026201220194008001.2k

Peers

Gérard Pierron
Comparison fields: 5 of 141
  • Physiology 673
  • Epidemiology 3.8k
  • Immunology 2.0k
  • Molecular Biology 6.4k
  • Cancer Research 1.4k
Replace Gian María Fimia with:
Gian María Fimia Italy
Jean‐Luc Perfettini France
Benjamin E. Turk United States
Suresh Subramani United States
Jörn Dengjel Germany
Didier Métivier France
Lixin Zheng United States
Adi Kimchi Israel
Fernando Macián United States
Sylvie Souquère France
Gérard Pierron relative to Gian María Fimia Italy Gian María Fimia's profile →
Citations per field
00.5×1.5×
Gian María Fimia · 1×
Citations per year

Countries citing papers authored by Gérard Pierron

Since Specialization
Citations

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

Fields of papers citing papers by Gérard Pierron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 202313
3 20232
4 20212
5 201924
6
Functional Domains of NEAT1 Architectural lncRNA Induce Paraspeckle Assembly through Phase Separation
Hit paper breakdown →
2018422
7 20172
8 20168
9 2015108
10 201446
11 201444
12 201419
13 2010177
14 20102
15 2009260
16 200967
17 2007109
18 20072
19 199912
20 19936

About Gérard Pierron

Gérard Pierron is a scholar working on Virology, Cell Biology, Molecular Biology, Biomaterials and Cancer Research, having authored 100 papers that have together received 10.9k indexed citations. Recurring topics across this work include Slime Mold and Myxomycetes Research (21 papers), Autophagy in Disease and Therapy (21 papers), RNA Research and Splicing (13 papers), Diatoms and Algae Research (12 papers), RNA modifications and cancer (11 papers), Chromosomal and Genetic Variations (10 papers), Cancer-related molecular mechanisms research (8 papers) and Endoplasmic Reticulum Stress and Disease (8 papers). The work is most often cited by research in Physiology (673 citations), Epidemiology (3.8k citations), Immunology (2.0k citations), Molecular Biology (6.4k citations) and Cancer Research (1.4k citations). Gérard Pierron has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Sylvie Souquère, Guido Kroemer, Francis Harper, Patrice Codogno, Didier Métivier, Noëlia Casares, Thiérry Heidmann, Rosa A. González‐Polo, Nathanaël Larochette and Patricia Boya. Their work appears in journals such as Experimental Cell Research, Nucleic Acids Research, Proceedings of the National Academy of Sciences, The EMBO Journal and Cell Cycle.

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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