Raphaële Thiébaut

608 total citations
16 papers, 283 citations indexed

About

Raphaële Thiébaut is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Cancer Research. According to data from OpenAlex, Raphaële Thiébaut has authored 16 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Pulmonary and Respiratory Medicine, 8 papers in Oncology and 5 papers in Cancer Research. Recurrent topics in Raphaële Thiébaut's work include Colorectal Cancer Treatments and Studies (8 papers), Lung Cancer Treatments and Mutations (7 papers) and Cancer Genomics and Diagnostics (4 papers). Raphaële Thiébaut is often cited by papers focused on Colorectal Cancer Treatments and Studies (8 papers), Lung Cancer Treatments and Mutations (7 papers) and Cancer Genomics and Diagnostics (4 papers). Raphaële Thiébaut collaborates with scholars based in France, United Kingdom and United States. Raphaële Thiébaut's co-authors include Jean‐Pierre Hugot, Leigh Pascoe, Pierre Laurent‐Puig, Patrick Lécine, Julie Perroy, Aurélie Hermant, Vincent Ollendorff, Camille Jung, Cendrine Nicoletti and Jean‐Paul Borg and has published in prestigious journals such as Journal of Clinical Investigation, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Raphaële Thiébaut

15 papers receiving 269 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Raphaële Thiébaut France 7 82 62 58 56 53 16 283
Daniel Fornika Canada 7 87 1.1× 33 0.5× 35 0.6× 68 1.2× 29 0.5× 11 271
Marianne van den Broek Netherlands 9 172 2.1× 77 1.2× 94 1.6× 83 1.5× 47 0.9× 12 466
Nejla Stambouli Tunisia 11 130 1.6× 32 0.5× 74 1.3× 79 1.4× 104 2.0× 25 304
Micha David Eichmann Switzerland 6 72 0.9× 44 0.7× 165 2.8× 64 1.1× 49 0.9× 6 296
Xiumin Huang China 9 107 1.3× 42 0.7× 53 0.9× 58 1.0× 29 0.5× 19 301
Eriko Okada Japan 8 83 1.0× 97 1.6× 64 1.1× 23 0.4× 150 2.8× 27 349
Sidney Santos Brazil 12 111 1.4× 150 2.4× 49 0.8× 65 1.2× 29 0.5× 23 455
Olivier Maillard France 11 137 1.7× 103 1.7× 38 0.7× 49 0.9× 41 0.8× 37 502
Eric McLaughlin United States 10 113 1.4× 81 1.3× 213 3.7× 32 0.6× 69 1.3× 61 396
A. Ido Japan 11 94 1.1× 108 1.7× 56 1.0× 24 0.4× 89 1.7× 18 357

Countries citing papers authored by Raphaële Thiébaut

Since Specialization
Citations

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

Fields of papers citing papers by Raphaële Thiébaut

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raphaële Thiébaut

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

All Works

16 of 16 papers shown
1.
Grégoire, V., Julien Labreuche, Hélène Béhal, et al.. (2024). 165P Consistency analysis of c-Met protein expression over time in patients with non-squamous non-small cell lung cancer. Annals of Oncology. 35. S282–S282. 1 indexed citations
2.
Laurent‐Puig, Pierre, Volker Heinemann, Daniel Neureiter, et al.. (2018). Validation of miR-31-3p Expression to Predict Cetuximab Efficacy When Used as First-Line Treatment in RAS Wild-Type Metastatic Colorectal Cancer. Clinical Cancer Research. 25(1). 134–141. 31 indexed citations
3.
4.
Pugh, S., Raphaële Thiébaut, John Bridgewater, et al.. (2017). Association between miR-31-3p expression and cetuximab efficacy in patients with KRAS wild-type metastatic colorectal cancer: a post-hoc analysis of the New EPOC trial. Oncotarget. 8(55). 93856–93866. 33 indexed citations
5.
Laurent‐Puig, Pierre, Volker Heinemann, Karine Fontaine, et al.. (2016). MiR-31-3p is a predictive biomarker of cetuximab response in FIRE3 clinical trial. Annals of Oncology. 27. vi151–vi151. 3 indexed citations
6.
Thiébaut, Raphaële, Patrick Lécine, Aurélie Hermant, et al.. (2016). Characterization and Genetic Analyses of New Genes Coding for NOD2 Interacting Proteins. PLoS ONE. 11(11). e0165420–e0165420. 81 indexed citations
7.
Laurent‐Puig, Pierre, Volker Heinemann, Franck Bonnetain, et al.. (2016). MiR 31 3p as a predictive biomarker of cetuximab efficacy effect in metastatic colorectal cancer (mCRC) patients enrolled in FIRE-3 study.. Journal of Clinical Oncology. 34(15_suppl). 3516–3516. 9 indexed citations
8.
Laurent‐Puig, Pierre, Sophie Paget‐Bailly, Déwi Vernerey, et al.. (2015). Evaluation of miR 31 3p as a biomarker of prognosis and panitumumab benefit in RAS-wt advanced colorectal cancer (aCRC): Analysis of patients (pts) from the PICCOLO trial.. Journal of Clinical Oncology. 33(15_suppl). 3547–3547. 6 indexed citations
9.
Bridgewater, John, S. Pugh, Karwan Moutasim, et al.. (2014). Analysis of progression-free survival in the new EPOC study in an “all wild-type” population.. Journal of Clinical Oncology. 32(15_suppl). 3566–3566. 2 indexed citations
10.
Laurent‐Puig, Pierre, John Bridgewater, John Primrose, et al.. (2014). Mir-31-3P is a Predictive Biomarker of Cetuximab Effects in a Post-Hoc Analysis in the New Epoc Study. Annals of Oncology. 25. iv185–iv185. 1 indexed citations
11.
Laurent‐Puig, Pierre, John Bridgewater, John Primrose, et al.. (2014). Mir-31-3p as a predictive biomarker of cetuximab effects in a post hoc analysis of new EPOC phase III trial.. Journal of Clinical Oncology. 32(15_suppl). 3523–3523. 2 indexed citations
12.
Manceau, Gilles, Jean‐Baptiste Bachet, Benoist Chibaudel, et al.. (2013). Hsa-miR-31-3p expression in FFPE tumor samples as a predictor of anti-EGFR response in patients with metastatic colorectal cancer.. Journal of Clinical Oncology. 31(15_suppl). 3562–3562. 1 indexed citations
13.
Jung, Camille, Ulrich Meinzer, Nicolas Montcuquet, et al.. (2012). Yersinia pseudotuberculosis disrupts intestinal barrier integrity through hematopoietic TLR-2 signaling. Journal of Clinical Investigation. 122(6). 2239–2251. 40 indexed citations
14.
Thiébaut, Raphaële, Salma Kotti, Camille Jung, et al.. (2009). TNFSF15 Polymorphisms Are Associated With Susceptibility to Inflammatory Bowel Disease in a New European Cohort. The American Journal of Gastroenterology. 104(2). 384–391. 60 indexed citations
15.
Pambrun, Élodie, Vincent Bouteloup, Victor de Lédinghen, et al.. (2009). 397 INDIVIDUAL PATIENT DATA META-ANALYSIS OF TRANSIENT ELASTOGRAPHY DIAGNOSTIC ACCURACY IN LIVER FIBROSIS ASSESSMENT OF CHRONIC HEPATITIS C PATIENTS (TE IPD STUDY). Journal of Hepatology. 50. S150–S150. 2 indexed citations
16.
Albertí, A., Nathan Clumeck, W.H. Gerlich, et al.. (2005). Short statement of the first european consensus conference on the treatment of chronic hepatitis B and C in HIV co-infected patients (vol 42, pg 615, 2005). Research Padua Archive (University of Padua). 43. 615–624. 1 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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