Dan Georgess

1.5k total citations · 1 hit paper
16 papers, 1.0k citations indexed

About

Dan Georgess is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Dan Georgess has authored 16 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 11 papers in Oncology and 4 papers in Genetics. Recurrent topics in Dan Georgess's work include Cancer Cells and Metastasis (7 papers), Bone health and treatments (4 papers) and Bone Metabolism and Diseases (3 papers). Dan Georgess is often cited by papers focused on Cancer Cells and Metastasis (7 papers), Bone health and treatments (4 papers) and Bone Metabolism and Diseases (3 papers). Dan Georgess collaborates with scholars based in United States, France and Lebanon. Dan Georgess's co-authors include Pierre Jurdic, Irma Machuca‐Gayet, Anne Blangy, Eszter Szarka, Georg Schett, Per‐Johan Jakobsson, Ulrike Harre, Lars Klareskog, Anca I. Catrina and Wolfgang Baum and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Bioinformatics.

In The Last Decade

Dan Georgess

15 papers receiving 1.0k 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.

Induction of osteoclastogenesis and bone loss by human autoantibodies against citrullinated vimentin

2012 544 citations Ulrike Harre, Dan Georgess et al. Journal of Clinical Investigation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dan Georgess United States	11	427	426	260	168	146	16	1.0k
Akeila Bellahcène Belgium	17	533 1.2×	322 0.8×	536 2.1×	43 0.3×	145 1.0×	22	1.1k
Rasesh Kapadia United States	13	612 1.4×	320 0.8×	428 1.6×	94 0.6×	87 0.6×	15	1.0k
Manali Bendre United States	7	551 1.3×	99 0.2×	578 2.2×	121 0.7×	78 0.5×	8	990
Echoe M. Bouta United States	16	232 0.5×	139 0.3×	626 2.4×	164 1.0×	39 0.3×	25	988
Jérôme Lemonnier France	19	941 2.2×	129 0.3×	514 2.0×	83 0.5×	50 0.3×	64	1.6k
Christiane Amendt Germany	12	440 1.0×	87 0.2×	294 1.1×	55 0.3×	58 0.4×	24	926
Changpu Yu United States	12	728 1.7×	67 0.2×	674 2.6×	186 1.1×	279 1.9×	22	1.5k
Verena Stresing France	12	390 0.9×	66 0.2×	432 1.7×	123 0.7×	144 1.0×	14	919
Ryotaro Iwasaki Japan	14	587 1.4×	218 0.5×	381 1.5×	180 1.1×	14 0.1×	21	1.0k
K. Yamaguchi Japan	10	835 2.0×	143 0.3×	591 2.3×	83 0.5×	39 0.3×	22	1.2k

Countries citing papers authored by Dan Georgess

Since Specialization

Citations

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

Fields of papers citing papers by Dan Georgess

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Georgess

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Georgess. A scholar is included among the top collaborators of Dan Georgess 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 Dan Georgess. Dan Georgess 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:

16 of 16 papers shown

1.

Wu, Yi‐Ying, et al.. (2025). Optimized chemical structure extends silencing duration of therapeutic siRNAs in dividing cancer and immune cells. Molecular Therapy. 33(11). 5791–5803.

2.

Padmanaban, Veena, Eloïse M. Grasset, Neil M. Neumann, et al.. (2020). Organotypic culture assays for murine and human primary and metastatic-site tumors. Nature Protocols. 15(8). 2413–2442. 48 indexed citations

3.

Fraser, Andrew K., Dan Georgess, Paul Macklin, et al.. (2020). OrgDyn: feature- and model-based characterization of spatial and temporal organoid dynamics. Bioinformatics. 36(10). 3292–3294. 8 indexed citations

4.

Georgess, Dan, et al.. (2019). Twist1-Induced Epithelial Dissemination Requires Prkd1 Signaling. Cancer Research. 80(2). 204–218. 23 indexed citations

5.

Xian, Lingling, Lionel Chia, Dan Georgess, et al.. (2019). Genetic Engineering of Primary Mouse Intestinal Organoids Using Magnetic Nanoparticle Transduction Viral Vectors for Frozen Sectioning. Journal of Visualized Experiments. 10 indexed citations

6.

Xian, Lingling, Lionel Chia, Dan Georgess, et al.. (2019). Genetic Engineering of Primary Mouse Intestinal Organoids Using Magnetic Nanoparticle Transduction Viral Vectors for Frozen Sectioning. Journal of Visualized Experiments. 8 indexed citations

7.

Georgess, Dan, Pirjo Spuul, Christophe Le Clainche, et al.. (2018). Anti-osteoclastic effects of C-glucosidic ellagitannins mediated by actin perturbation. European Journal of Cell Biology. 97(8). 533–545. 6 indexed citations

8.

Xian, Lingling, Dan Georgess, Tait Huso, et al.. (2017). HMGA1 amplifies Wnt signalling and expands the intestinal stem cell compartment and Paneth cell niche. Nature Communications. 8(1). 15008–15008. 64 indexed citations

9.

Asrani, Kaushal, Anil K. Sood, Alba Torres, et al.. (2017). mTORC1 loss impairs epidermal adhesion via TGF-β/Rho kinase activation. Journal of Clinical Investigation. 127(11). 4001–4017. 27 indexed citations

10.

Silvestri, Vanesa L., et al.. (2017). Mosaic loss of non-muscle myosin IIA and IIB is sufficient to induce mammary epithelial proliferation. Journal of Cell Science. 130(19). 3213–3221. 12 indexed citations

11.

Shamir, Eliah R., et al.. (2016). Twist1-positive epithelial cells retain adhesive and proliferative capacity throughout dissemination. Biology Open. 5(9). 1216–1228. 9 indexed citations

12.

Allard, Lise, Irma Machuca‐Gayet, Dan Georgess, et al.. (2015). Biphasic Effects of Vitamin D and FGF23 on Human Osteoclast Biology. Calcified Tissue International. 97(1). 69–79. 34 indexed citations

13.

Georgess, Dan, Irma Machuca‐Gayet, Anne Blangy, & Pierre Jurdic. (2014). Podosome organization drives osteoclast-mediated bone resorption. Cell Adhesion & Migration. 8(3). 192–204. 147 indexed citations

14.

Georgess, Dan, M. Mazzorana, José Terrado, et al.. (2013). Comparative transcriptomics reveals RhoE as a novel regulator of actin dynamics in bone-resorbing osteoclasts. Molecular Biology of the Cell. 25(3). 380–396. 35 indexed citations

15.

Harre, Ulrike, Dan Georgess, Holger Bang, et al.. (2012). Induction of osteoclastogenesis and bone loss by human autoantibodies against citrullinated vimentin. Journal of Clinical Investigation. 122(5). 1791–1802. 544 indexed citations breakdown →

16.

Hu, Shiqiong, Emmanuelle Planus, Dan Georgess, et al.. (2011). Podosome rings generate forces that drive saltatory osteoclast migration. Molecular Biology of the Cell. 22(17). 3120–3126. 34 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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