Fanny Fava

492 total citations
8 papers, 200 citations indexed

About

Fanny Fava is a scholar working on Hematology, Oncology and Molecular Biology. According to data from OpenAlex, Fanny Fava has authored 8 papers receiving a total of 200 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Hematology, 4 papers in Oncology and 3 papers in Molecular Biology. Recurrent topics in Fanny Fava's work include Acute Myeloid Leukemia Research (3 papers), Peptidase Inhibition and Analysis (2 papers) and Protease and Inhibitor Mechanisms (2 papers). Fanny Fava is often cited by papers focused on Acute Myeloid Leukemia Research (3 papers), Peptidase Inhibition and Analysis (2 papers) and Protease and Inhibitor Mechanisms (2 papers). Fanny Fava collaborates with scholars based in France and Tunisia. Fanny Fava's co-authors include Ruoping Tang, Ollivier Legrand, Simona Lapusan, Pierre Hirsch, Sandrine Bouchet, Brigitte Bauvois, Christophe Marzac, Chloé James, Frédéric Mazurier and Carole Tonetti and has published in prestigious journals such as Blood, Oncotarget and Haematologica.

In The Last Decade

Fanny Fava

8 papers receiving 195 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fanny Fava France	6	129	97	94	34	32	8	200
Jennifer Cassels United Kingdom	7	166 1.3×	95 1.0×	94 1.0×	39 1.1×	43 1.3×	17	250
Linda Gojenola United States	3	135 1.0×	80 0.8×	140 1.5×	52 1.5×	17 0.5×	5	211
Tiago Maié Germany	7	69 0.5×	99 1.0×	61 0.6×	25 0.7×	23 0.7×	17	181
Wanke Zhao United States	8	95 0.7×	91 0.9×	87 0.9×	36 1.1×	18 0.6×	14	182
Eleni Louka United Kingdom	2	99 0.8×	166 1.7×	70 0.7×	35 1.0×	32 1.0×	5	238
Kathleen C. Rayeroux Australia	6	109 0.8×	109 1.1×	91 1.0×	37 1.1×	50 1.6×	10	224
Bárbara da Costa Reis Monte-Mór Brazil	8	172 1.3×	267 2.8×	144 1.5×	33 1.0×	49 1.5×	19	367
Fiona Watkins United Kingdom	6	246 1.9×	180 1.9×	117 1.2×	18 0.5×	38 1.2×	8	379
Ruzhica Bogeska Germany	6	139 1.1×	108 1.1×	86 0.9×	16 0.5×	25 0.8×	8	235
Caroline J. Watson United Kingdom	3	167 1.3×	115 1.2×	94 1.0×	18 0.5×	19 0.6×	5	290

Countries citing papers authored by Fanny Fava

Since Specialization

Citations

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

Fields of papers citing papers by Fanny Fava

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fanny Fava

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

All Works

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8 of 8 papers shown

1.

Lamarthée, Baptiste, Florent Malard, Nicolas Stocker, et al.. (2018). Quantitative and functional alterations of 6-sulfo LacNac dendritic cells in multiple myeloma. OncoImmunology. 7(7). e1444411–e1444411. 6 indexed citations

2.

Hirsch, Pierre, Ruoping Tang, Nasséra Abermil, et al.. (2017). Precision and prognostic value of clone-specific minimal residual disease in acute myeloid leukemia. Haematologica. 102(7). 1227–1237. 38 indexed citations

3.

Besbes, Souhail, Hamda Al-Thawadi, Ruoping Tang, et al.. (2015). Endothelial protein C receptor gene 6936A/G single-nucleotide polymorphism as a possible biomarker of thrombotic risk in acute myeloid leukemia. Molecular and Clinical Oncology. 3(6). 1280–1284. 2 indexed citations

4.

Bouchet, Sandrine, Ruoping Tang, Fanny Fava, Ollivier Legrand, & Brigitte Bauvois. (2015). The CNGRC-GG-D(KLAKLAK)2 peptide induces a caspase-independent, Ca2+-dependent death in human leukemic myeloid cells by targeting surface aminopeptidase N/CD13. Oncotarget. 7(15). 19445–19467. 24 indexed citations

5.

Bouchet, Sandrine, Ruoping Tang, Fanny Fava, Ollivier Legrand, & Brigitte Bauvois. (2014). Targeting CD13 (aminopeptidase-N) in turn downregulates ADAM17 by internalization in acute myeloid leukaemia cells. Oncotarget. 5(18). 8211–8222. 11 indexed citations

6.

Hirsch, Pierre, Ruoping Tang, Christophe Marzac, et al.. (2010). ABC Proteins Activity Remains An Independent Prognostic Factor In 206 AML When Compared to Other Molecular Markers, FLT3, NPM1, CEBPα, and BAALC. Blood. 116(21). 1698–1698. 1 indexed citations

7.

Tang, Ruoping, Pierre Hirsch, Fanny Fava, et al.. (2009). High Id1 expression is associated with poor prognosis in 237 patients with acute myeloid leukemia. Blood. 114(14). 2993–3000. 43 indexed citations

8.

Chaligné, Ronan, Chloé James, Carole Tonetti, et al.. (2007). Evidence for MPL W515L/K mutations in hematopoietic stem cells in primitive myelofibrosis. Blood. 110(10). 3735–3743. 75 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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