Mathieu Courcelles
- Immunology top 5%
- Immunotherapy and Immune Responses 10
- Molecular Biology top 10%
- vaccines and immunoinformatics approaches 9
- Glycosylation and Glycoproteins Research 3
- Ubiquitin and proteasome pathways 3
- Oncology top 10%
- Peptidase Inhibition and Analysis 7
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications 6
- Mass Spectrometry Techniques and Applications 4
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- Monoclonal and Polyclonal Antibodies Research 5
- Co-authors
- Pierre ThibaultSébastien LemieuxÉric BonneilClaude PerreaultChantal DuretteCaroline CôtéJoël LanoixMichel Desjardins
- Cited by
- ImmunologyMolecular BiologyOncology
- Journals
- Journal of Proteome Research (4 papers)Molecular & Cellular Proteomics (4 papers)Cell Reports (2 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Mathieu Courcelles
25 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Immunology 595
- Molecular Biology 1.1k
- Oncology 424
- Spectroscopy 186
- Radiology, Nuclear Medicine and Imaging 151
Countries citing papers authored by Mathieu Courcelles
This map shows the geographic impact of Mathieu Courcelles'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 Mathieu Courcelles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathieu Courcelles more than expected).
Fields of papers citing papers by Mathieu Courcelles
This network shows the impact of papers produced by Mathieu Courcelles. 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 Mathieu Courcelles. The network helps show where Mathieu Courcelles may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mathieu Courcelles, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 13 | |
| 2 | 2023 | 9 | |
| 3 | 2022 | 12 | |
| 4 | 2022 | 3 | |
| 5 | 2022 | 24 | |
| 6 | 2021 | 1 | |
| 7 | 2021 | 115 | |
| 8 | 2020 | 52 | |
| 9 | 2020 | 41 | |
| 10 | 2020 | 9 | |
| 11 | Noncoding regions are the main source of targetable tumor-specific antigensbreakdown → | 2018 | 335 |
| 12 | 2018 | 52 | |
| 13 | 2016 | 122 | |
| 14 | 2013 | 93 | |
| 15 | 2012 | 26 | |
| 16 | 2011 | 23 | |
| 17 | 2010 | 125 | |
| 18 | 2009 | 191 | |
| 19 | 2008 | 20 | |
| 20 | 2007 | 55 |
About Mathieu Courcelles
Mathieu Courcelles is a scholar working on Immunology, Spectroscopy and Molecular Biology, having authored 25 papers that have together received 1.5k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (10 papers), vaccines and immunoinformatics approaches (9 papers), Peptidase Inhibition and Analysis (7 papers), Advanced Proteomics Techniques and Applications (6 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Mass Spectrometry Techniques and Applications (4 papers), Glycosylation and Glycoproteins Research (3 papers) and Ubiquitin and proteasome pathways (3 papers). The work is most often cited by research in Immunology (595 citations), Molecular Biology (1.1k citations) and Oncology (424 citations). Mathieu Courcelles has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Pierre Thibault, Sébastien Lemieux, Éric Bonneil, Claude Perreault, Chantal Durette, Caroline Côté, Joël Lanoix, Michel Desjardins, Matthias Trost and Marie‐Pierre Hardy. Their work appears in journals such as Journal of Proteome Research, Molecular & Cellular Proteomics, Cell Reports, Journal of Clinical Investigation and PROTEOMICS.
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.