A Haeffner

1.1k total citations · 1 hit paper
7 papers, 930 citations indexed

About

A Haeffner is a scholar working on Endocrinology, Diabetes and Metabolism, Immunology and Molecular Biology. According to data from OpenAlex, A Haeffner has authored 7 papers receiving a total of 930 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Endocrinology, Diabetes and Metabolism, 3 papers in Immunology and 2 papers in Molecular Biology. Recurrent topics in A Haeffner's work include Growth Hormone and Insulin-like Growth Factors (4 papers), Cell death mechanisms and regulation (2 papers) and interferon and immune responses (1 paper). A Haeffner is often cited by papers focused on Growth Hormone and Insulin-like Growth Factors (4 papers), Cell death mechanisms and regulation (2 papers) and interferon and immune responses (1 paper). A Haeffner collaborates with scholars based in France and Morocco. A Haeffner's co-authors include François Hirsch, Tamara Hirsch, Antonio Macho, Philippe Marchetti, Maurice Geuskens, Guido Kroemer, Santos A. Susín, Naoufal Zamzami, Nicole Haeffner‐Cavaillon and Nathalie Thiéblemont and has published in prestigious journals such as The Journal of Experimental Medicine, The Journal of Immunology and British Journal of Cancer.

In The Last Decade

A Haeffner

7 papers receiving 910 citations

Hit Papers

Mitochondrial permeability transition is a central coordi... 1996 2026 2006 2016 1996 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A Haeffner France 6 636 203 109 99 74 7 930
Stanley J. Wertheimer United States 12 449 0.7× 228 1.1× 75 0.7× 116 1.2× 67 0.9× 19 888
Hebok Song South Korea 16 632 1.0× 122 0.6× 71 0.7× 114 1.2× 92 1.2× 22 1.0k
R Mosselmans Belgium 12 484 0.8× 219 1.1× 139 1.3× 108 1.1× 110 1.5× 16 966
Jonny Wijkander Sweden 22 793 1.2× 228 1.1× 119 1.1× 98 1.0× 62 0.8× 29 1.2k
H. Mutoh Japan 13 346 0.5× 131 0.6× 94 0.9× 39 0.4× 53 0.7× 24 800
T Deng United States 11 696 1.1× 94 0.5× 155 1.4× 99 1.0× 36 0.5× 15 926
Diane M Spencer United States 15 712 1.1× 229 1.1× 74 0.7× 94 0.9× 91 1.2× 24 1.2k
Fatemeh Karami‐Tehrani Iran 20 648 1.0× 153 0.8× 205 1.9× 151 1.5× 60 0.8× 27 1.1k
Roderick G. Davis United States 10 791 1.2× 85 0.4× 107 1.0× 99 1.0× 92 1.2× 13 1.1k
Margot Grandl Germany 16 460 0.7× 234 1.2× 82 0.8× 97 1.0× 121 1.6× 25 835

Countries citing papers authored by A Haeffner

Since Specialization
Citations

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

Fields of papers citing papers by A Haeffner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A Haeffner

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

All Works

7 of 7 papers shown
1.
Déas, Olivier, Gilles Vassal, Antoine Dürrbach, et al.. (2003). Potentiation of tumour apoptosis by human growth hormone via glutathione production and decreased NF-κB activity. British Journal of Cancer. 89(6). 1108–1115. 10 indexed citations
2.
Déas, Olivier, Gilles Vassal, Jean‐Louis Merlin, et al.. (2002). Human growth hormone gene transfer into tumor cells may improve cancer chemotherapy. Cancer Gene Therapy. 9(6). 497–504. 9 indexed citations
3.
Haeffner, A, Olivier Déas, Bertrand Mollereau, et al.. (1999). Growth hormone prevents human monocytic cells from Fas-mediated apoptosis by up-regulating Bcl-2 expression. European Journal of Immunology. 29(1). 334–344. 43 indexed citations
4.
Haeffner, A, Olivier Déas, Bertrand Mollereau, et al.. (1999). Growth hormone prevents human monocytic cells from Fas-mediated apoptosis by up-regulating Bcl-2 expression. European Journal of Immunology. 29(1). 334–344. 4 indexed citations
5.
Haeffner, A, Nathalie Thiéblemont, Olivier Déas, et al.. (1997). Inhibitory effect of growth hormone on TNF-α secretion and nuclear factor-kappaB translocation in lipopolysaccharide-stimulated human monocytes. The Journal of Immunology. 158(3). 1310–1314. 53 indexed citations
6.
Marchetti, Philippe, Santos A. Susín, Naoufal Zamzami, et al.. (1996). Mitochondrial permeability transition is a central coordinating event of apoptosis.. The Journal of Experimental Medicine. 184(3). 1155–1160. 753 indexed citations breakdown →
7.
Thiéblemont, Nathalie, Nicole Haeffner‐Cavaillon, A Haeffner, et al.. (1995). Triggering of complement receptors CR1 (CD35) and CR3 (CD11b/CD18) induces nuclear translocation of NF-kappa B (p50/p65) in human monocytes and enhances viral replication in HIV-infected monocytic cells. The Journal of Immunology. 155(10). 4861–4867. 58 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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