Franck Giacomoni

1.2k total citations
12 papers, 479 citations indexed

About

Franck Giacomoni is a scholar working on Molecular Biology, Spectroscopy and Neurology. According to data from OpenAlex, Franck Giacomoni has authored 12 papers receiving a total of 479 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Spectroscopy and 1 paper in Neurology. Recurrent topics in Franck Giacomoni's work include Metabolomics and Mass Spectrometry Studies (11 papers), Bioinformatics and Genomic Networks (7 papers) and Advanced Proteomics Techniques and Applications (4 papers). Franck Giacomoni is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (11 papers), Bioinformatics and Genomic Networks (7 papers) and Advanced Proteomics Techniques and Applications (4 papers). Franck Giacomoni collaborates with scholars based in France, Austria and United Kingdom. Franck Giacomoni's co-authors include Mélanie Pétéra, Christophe Dupérier, Marie Tremblay‐Franco, Etienne Thévenot, Jean‐François Martin, Christophe Caron, Gildas Le Corguillé, Sophie Goulitquer, Daniel Jacob and Pierre Péricard and has published in prestigious journals such as Bioinformatics, Analytical Chemistry and TrAC Trends in Analytical Chemistry.

In The Last Decade

Franck Giacomoni

11 papers receiving 474 citations

Peers

Franck Giacomoni
Komal Kanojia Australia
Timothy Sangster United Kingdom
Andy Tseng United Kingdom
Sara Forcisi Germany
Steve Oliver United Kingdom
Clare A. Daykin United Kingdom
Franck Giacomoni
Citations per year, relative to Franck Giacomoni Franck Giacomoni (= 1×) peers Christophe Dupérier

Countries citing papers authored by Franck Giacomoni

Since Specialization
Citations

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

Fields of papers citing papers by Franck Giacomoni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Franck Giacomoni

This figure shows the co-authorship network connecting the top 25 collaborators of Franck Giacomoni. A scholar is included among the top collaborators of Franck Giacomoni 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 Franck Giacomoni. Franck Giacomoni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Delporte, Cédric, Marie Tremblay‐Franco, Yann Guitton, et al.. (2025). Workflow4Metabolomics (W4M): A User‐Friendly Metabolomics Platform for Analysis of Mass Spectrometry and Nuclear Magnetic Resonance Data. Current Protocols. 5(2). e70095–e70095.
2.
Cabanac, Guillaume, Yann Guitton, Bernard Lyan, et al.. (2024). FragHub: A Mass Spectral Library Data Integration Workflow. Analytical Chemistry. 7 indexed citations
3.
Witting, Michael, Adnan Malik, Andrew R. Leach, et al.. (2024). Challenges and perspectives for naming lipids in the context of lipidomics. Metabolomics. 20(1). 15–15. 4 indexed citations
4.
Santos, Millena Cristina Barros, Justine Bertrand‐Michel, Cécile Canlet, et al.. (2023). Scaling-up metabolomics: Current state and perspectives. TrAC Trends in Analytical Chemistry. 167. 117225–117225. 20 indexed citations
6.
Dupérier, Christophe, Florence Vinson, Pablo Rodríguez-Mier, et al.. (2022). Suggesting disease associations for overlooked metabolites using literature from metabolic neighbors. GigaScience. 12. 1 indexed citations
7.
Vinson, Florence, et al.. (2021). FORUM: building a Knowledge Graph from public databases and scientific literature to extract associations between chemicals and diseases. Bioinformatics. 37(21). 3896–3904. 7 indexed citations
8.
Gloaguen, Yoann, Eric Blanc, Anne‐Lise Royer, et al.. (2019). WiPP: Workflow for Improved Peak Picking for Gas Chromatography-Mass Spectrometry (GC-MS) Data. Metabolites. 9(9). 171–171. 20 indexed citations
9.
Guitton, Yann, Marie Tremblay‐Franco, Gildas Le Corguillé, et al.. (2017). Create, run, share, publish, and reference your LC–MS, FIA–MS, GC–MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics. The International Journal of Biochemistry & Cell Biology. 93. 89–101. 97 indexed citations
10.
Vinson, Florence, Clément Frainay, Nathalie Poupin, et al.. (2016). A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks. Frontiers in Molecular Biosciences. 3. 2–2. 3 indexed citations
11.
Lyan, Bernard, Charlotte Joly, Delphine Centeno, et al.. (2015). Assessment of protein modifications in liver of rats under chronic treatment with paracetamol (acetaminophen) using two complementary mass spectrometry-based metabolomic approaches. Journal of Proteomics. 120. 194–203. 8 indexed citations
12.
Giacomoni, Franck, Gildas Le Corguillé, Pierre Péricard, et al.. (2014). Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics. Bioinformatics. 31(9). 1493–1495. 301 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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