C. Libenciuc

1.5k total citations · 1 hit paper
7 papers, 921 citations indexed

About

C. Libenciuc is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, C. Libenciuc has authored 7 papers receiving a total of 921 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Oncology and 2 papers in Immunology. Recurrent topics in C. Libenciuc's work include Cancer Immunotherapy and Biomarkers (4 papers), CAR-T cell therapy research (3 papers) and Melanoma and MAPK Pathways (3 papers). C. Libenciuc is often cited by papers focused on Cancer Immunotherapy and Biomarkers (4 papers), CAR-T cell therapy research (3 papers) and Melanoma and MAPK Pathways (3 papers). C. Libenciuc collaborates with scholars based in France and United States. C. Libenciuc's co-authors include Caroline Robert, Émilie Routier, Christine Mateus, Jean‐Charles Soria, Aurélien Marabelle, Émilie Lanoy, Olivier Lambotte, Alexander M.M. Eggermont, Franck Carbonnel and Stéphane Champiat and has published in prestigious journals such as Annals of Oncology, Cell Reports and Nature Reviews Clinical Oncology.

In The Last Decade

C. Libenciuc

7 papers receiving 916 citations

Hit Papers

align trajectories

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.

Safety profiles of anti-CTLA-4 and anti-PD-1 antibodies alone and in combination

2016 813 citations C. Boutros, Ahmad A. Tarhini et al. Nature Reviews Clinical Oncology profile →

Peers

C. Libenciuc

ONCOL

IMMUN

MB

PRM

BE

Yavar Shiravand Italy

Prakash Kharel United States

Faezeh Khodadadi Iran

Habib Sadeghirad Australia

Raju Vaddepally United States

Zipei Feng United States

Yongsheng Wang China

Aixa Soyano United States

Michitaka Nakano Japan

Gayathri Anandappa United Kingdom

Yavar Shiravand Italy

C. Libenciuc

493 ×0.7

ONCOL

285 ×0.8

IMMUN

214 ×1.1

MB

147 ×1.0

PRM

60 ×0.8

BE

Citations per year, relative to C. Libenciuc C. Libenciuc (= 1×) peers Yavar Shiravand

Countries citing papers authored by C. Libenciuc

Since Specialization

Citations

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

Fields of papers citing papers by C. Libenciuc

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of C. Libenciuc

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Shen, Shensi, Sara Faouzi, Sylvie Souquère, et al.. (2020). Melanoma Persister Cells Are Tolerant to BRAF/MEK Inhibitors via ACOX1-Mediated Fatty Acid Oxidation. Cell Reports. 33(8). 108421–108421. 100 indexed citations

2.

Shen, Shensi, Sara Faouzi, Sylvie Souquère, et al.. (2020). Melanoma Persister Cells are Tolerant to BRAF/MEK Inhibitors Via ACOX1-Mediated Fatty Acid Oxidation. SSRN Electronic Journal. 3 indexed citations

3.

Boutros, C., Émilie Routier, Camille Hua, et al.. (2016). Detailed safety profile of the anti-PD-1 monoclonal antibody pembrolizumab in 78 consecutive patients (pts) with advanced melanoma. Annals of Oncology. 27. vi385–vi385. 1 indexed citations

4.

Boutros, C., Christine Mateus, Émilie Routier, et al.. (2016). A dose escalation phase 1 study of radiotherapy (RT) in combination with anti-cytotoxic-T-lymphocyte-associated antigen 4 (CTLA-4) monoclonal antibody ipilimumab (Ipi) in patients (pts) with metastatic melanoma. Annals of Oncology. 27. vi383–vi383. 2 indexed citations

5.

Boutros, C., Ahmad A. Tarhini, Émilie Routier, et al.. (2016). Safety profiles of anti-CTLA-4 and anti-PD-1 antibodies alone and in combination. Nature Reviews Clinical Oncology. 13(8). 473–486. 813 indexed citations breakdown →

6.

Mateus, Christine, Olaf Mercier, P. Dufour, et al.. (2016). Cancers secondaires sous immunothérapies dans un contexte de mélanome métastatique. Annales de Dermatologie et de Vénéréologie. 143(12). S365–S366. 1 indexed citations

7.

Libenciuc, C., Céu Mateus, Émilie Routier, et al.. (2016). Neuropathies sensitives sous la combinaison inhibiteurs de BRAF et de MEK : dabrafénib et tramétinib. Annales de Dermatologie et de Vénéréologie. 143(12). S207–S207. 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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