Daniel Soppet

1.6k citations
9 papers · 170 · h-index 7

Impact in

    • Skin and Cellular Biology Research
    • Cellular Mechanics and Interactions
    • Microtubule and mitosis dynamics
    • Cellular transport and secretion
    • Pharmacogenetics and Drug Metabolism

Papers in

Daniel Soppet

8 papers receiving 168 citations

Peers

Daniel Soppet
Comparison fields: 5 of 64
  • Cell Biology 71
  • Pharmacology 11
  • Developmental Neuroscience 5
  • Cellular and Molecular Neuroscience 19
  • Molecular Biology 66
Replace Soo‐Kyung Suh with:
Soo‐Kyung Suh United States
Ezequiel Campos‐Mollo Spain
Chukai Huang Hong Kong
Mari Asada Japan
Christian Oertlin Sweden
Ah Jung Heo South Korea
S Rogers United Kingdom
Waka Kojima Japan
Henning Wiegmann Germany
Sara Isaac Israel
Daniel Soppet relative to Soo‐Kyung Suh United States Soo‐Kyung Suh's profile →
Citations per field
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Soo‐Kyung Suh · 1×
Citations per year

Countries citing papers authored by Daniel Soppet

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Soppet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 198763
2 201437
3 202218
4 199016
5 201716
6 19818
7 20207
8 20145
9 20240

About Daniel Soppet

Daniel Soppet is a scholar working on Molecular Biology, Pediatrics, Perinatology and Child Health, Cell Biology, Genetics and Oncology, having authored 9 papers that have together received 170 indexed citations. Recurring topics across this work include Metabolism and Genetic Disorders (1 paper), Machine Learning in Bioinformatics (1 paper), Cellular Mechanics and Interactions (1 paper), Hemoglobinopathies and Related Disorders (1 paper), Neonatal Health and Biochemistry (1 paper), Computational Drug Discovery Methods (1 paper), Cancer-related Molecular Pathways (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Cell Biology (71 citations), Pharmacology (11 citations), Developmental Neuroscience (5 citations), Cellular and Molecular Neuroscience (19 citations) and Molecular Biology (66 citations). Daniel Soppet has collaborated with scholars based in United States, India and Ukraine. Frequent co-authors include Mark Willard, Marcie A. Glicksman, David R. Whikehart, Paul S. Changelian, Karina F. Meiri, A Loewy, Harold W. Jaffe, Sam M. Mbulaiteye, Nyengo Mkandawire and Steve Kamiza. Their work appears in journals such as Scientific Reports, The Journal of Clinical Pharmacology, Current Eye Research, Brain Research and International Journal of Molecular Sciences.

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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