Nicolas Pasqual

1.8k total citations · 1 hit paper
17 papers, 1.3k citations indexed

About

Nicolas Pasqual is a scholar working on Immunology, Oncology and Genetics. According to data from OpenAlex, Nicolas Pasqual has authored 17 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 6 papers in Oncology and 4 papers in Genetics. Recurrent topics in Nicolas Pasqual's work include T-cell and B-cell Immunology (8 papers), Immune Cell Function and Interaction (8 papers) and Immunotherapy and Immune Responses (6 papers). Nicolas Pasqual is often cited by papers focused on T-cell and B-cell Immunology (8 papers), Immune Cell Function and Interaction (8 papers) and Immunotherapy and Immune Responses (6 papers). Nicolas Pasqual collaborates with scholars based in France, United States and Switzerland. Nicolas Pasqual's co-authors include Solène Perez, Christophe Caux, Christine Ménétrier‐Caux, Thomas Bachelot, Jean‐Yves Blay, Isabelle Ray‐Coquard, Cathy Biota, Manuarii Manuel, Sophie Goddard‐Léon and Nathalie Bendriss‐Vermare and has published in prestigious journals such as The Journal of Experimental Medicine, Cancer Research and European Heart Journal.

In The Last Decade

Nicolas Pasqual

17 papers receiving 1.3k citations

Hit Papers

Regulatory T Cells Recruited through CCL22/CCR4 Are Selec... 2009 2026 2014 2020 2009 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Regulatory T Cells Recruited through CCL22/CCR4 Are Selectively Activated in Lymphoid Infiltrates Surrounding Primary Breast Tumors and Lead to an Adverse Clinical Outcome
    2009 562 citations Michael Gobert, Isabelle Treilleux et al. Cancer Research profile →

Peers

Nicolas Pasqual
In-Hak Choi South Korea
Sonia Pastor France
Annelie Vulink Netherlands
Debora Martorelli Italy
Murali Janakiram United States
Amer Assal United States
Vittore Cereda Italy
James Strauss United States
Frederick R. Aronson United States
Arcadi Cipponi Italy
In-Hak Choi South Korea
Nicolas Pasqual
Citations per year, relative to Nicolas Pasqual Nicolas Pasqual (= 1×) peers In-Hak Choi

Countries citing papers authored by Nicolas Pasqual

Since Specialization
Citations

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

Fields of papers citing papers by Nicolas Pasqual

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolas Pasqual

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

All Works

17 of 17 papers shown
1.
Hogan, Sabrina A., Anaïs Courtier, Phil F. Cheng, et al.. (2018). Peripheral Blood TCR Repertoire Profiling May Facilitate Patient Stratification for Immunotherapy against Melanoma. Cancer Immunology Research. 7(1). 77–85. 100 indexed citations
2.
Postow, Michael A., Manuarii Manuel, Phillip Wong, et al.. (2015). Peripheral T cell receptor diversity is associated with clinical outcomes following ipilimumab treatment in metastatic melanoma. Journal for ImmunoTherapy of Cancer. 3(1). 23–23. 172 indexed citations
3.
Klingenberg, Roland, Chad E. Brokopp, Anaïs Courtier, et al.. (2014). Clonal restriction and predominance of regulatory T cells in coronary thrombi of patients with acute coronary syndromes. European Heart Journal. 36(17). 1041–1048. 43 indexed citations
4.
Postow, Michael A., Manuarii Manuel, Phillip Wong, et al.. (2014). T cell receptor diversity evaluation to predict patient response to Ipilimumab in metastatic melanoma. Journal for ImmunoTherapy of Cancer. 2(S3). 2 indexed citations
5.
Trédan, Olivier, Manuarii Manuel, Gilles Clapisson, et al.. (2012). Patients with metastatic breast cancer leading to CD4+ T cell lymphopaenia have poor outcome. European Journal of Cancer. 49(7). 1673–1682. 44 indexed citations
6.
Venet, Fabienne, Orchidée Filipe‐Santos, Alain Lepape, et al.. (2012). Decreased T-Cell Repertoire Diversity in Sepsis. Critical Care Medicine. 41(1). 111–119. 61 indexed citations
7.
Manuel, Manuarii, Olivier Trédan, Thomas Bachelot, et al.. (2012). Lymphopenia combined with low TCR diversity (divpenia) predicts poor overall survival in metastatic breast cancer patients. OncoImmunology. 1(4). 432–440. 101 indexed citations
8.
Manuel, Manuarii, Olivier Trédan, Thomas Bachelot, et al.. (2011). Abstract LB-165: Low TCR diversity (divpenia) is a new prognosis factor of overall survival in metastatic breast cancer. Cancer Research. 71(8_Supplement). LB–165. 1 indexed citations
9.
Derouazi, Madiha, Yan Wang, Raphaël Marlu, et al.. (2010). Optimal epitope composition after antigen screening using a live bacterial delivery vector. PubMed. 1(1). 51–60. 19 indexed citations
10.
Pasqual, Nicolas, et al.. (2010). Numerical Modelling Of The V-J Combinations Of The T Cell Receptor TRA/TRD Locus. PLoS Computational Biology. 6(2). e1000682–e1000682. 14 indexed citations
11.
Gobert, Michael, Isabelle Treilleux, Nathalie Bendriss‐Vermare, et al.. (2009). Regulatory T Cells Recruited through CCL22/CCR4 Are Selectively Activated in Lymphoid Infiltrates Surrounding Primary Breast Tumors and Lead to an Adverse Clinical Outcome. Cancer Research. 69(5). 2000–2009. 562 indexed citations breakdown →
12.
Marodon, Gilles, Delphine Desjardins, Claude Baillou, et al.. (2009). High diversity of the immune repertoire in humanized NOD.SCID.γc−/− mice. European Journal of Immunology. 39(8). 2136–2145. 45 indexed citations
13.
Fuschiotti, Patrizia, Nicolas Pasqual, Eve Borel, et al.. (2007). Analysis of the TCR α-chain rearrangement profile in human T lymphocytes. Molecular Immunology. 44(13). 3380–3388. 18 indexed citations
14.
Pasqual, Nicolas, Fatena Bellahcene, Denys Chaume, et al.. (2006). IMGT/GeneInfo: T cell receptor gamma TRG and delta TRD genes in database give access to all TR potential V(D)J recombinations. BMC Bioinformatics. 7(1). 224–224. 19 indexed citations
15.
Bosco, Nabil, Hsiu‐Cheng Hung, Nicolas Pasqual, et al.. (2005). Role of the T cell receptor alpha chain in the development and phenotype of naturally arising CD4CD25 T cells. Molecular Immunology. 43(3). 246–254. 7 indexed citations
16.
Pasqual, Nicolas, Catherine Aude‐Garcia, Mélanie Loiodice, et al.. (2002). Quantitative and Qualitative Changes in V-J α Rearrangements During Mouse Thymocytes Differentiation. The Journal of Experimental Medicine. 196(9). 1163–1174. 71 indexed citations
17.
Riva, Catherine, et al.. (2001). Bcl-2/Bax protein expression in heart, slow-twitch and fast-twitch muscles in young rats growing under chronic hypoxia conditions. Molecular and Cellular Biochemistry. 226(1-2). 9–16. 14 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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