Cathy Savage‐Dunn

1.5k total citations
36 papers, 1.1k citations indexed

About

Cathy Savage‐Dunn is a scholar working on Aging, Molecular Biology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Cathy Savage‐Dunn has authored 36 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Aging, 20 papers in Molecular Biology and 10 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Cathy Savage‐Dunn's work include Genetics, Aging, and Longevity in Model Organisms (33 papers), Reproductive Biology and Fertility (10 papers) and Pluripotent Stem Cells Research (8 papers). Cathy Savage‐Dunn is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (33 papers), Reproductive Biology and Fertility (10 papers) and Pluripotent Stem Cells Research (8 papers). Cathy Savage‐Dunn collaborates with scholars based in United States, Netherlands and Canada. Cathy Savage‐Dunn's co-authors include Richard W. Padgett, Rafal Tokarz, Jianjun Wang, Robert M. Ross, William B. Wood, Yo Suzuki, Mark Yandell, Peter J. Roy, Ling Yu and David H. Hall and has published in prestigious journals such as PLoS ONE, Development and Genetics.

In The Last Decade

Cathy Savage‐Dunn

35 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cathy Savage‐Dunn United States	17	711	519	181	134	121	36	1.1k
Masamitsu Fukuyama Japan	11	455 0.6×	418 0.8×	177 1.0×	80 0.6×	90 0.7×	20	723
Kiyokazu Morita Japan	10	377 0.5×	523 1.0×	85 0.5×	71 0.5×	38 0.3×	12	788
Siming Ma United States	17	332 0.5×	509 1.0×	61 0.3×	38 0.3×	214 1.8×	22	1.2k
Shijing Luo United States	8	453 0.6×	290 0.6×	212 1.2×	64 0.5×	147 1.2×	10	690
Barbara Goszczynski Canada	13	577 0.8×	482 0.9×	150 0.8×	63 0.5×	60 0.5×	17	748
Sudhir Nayak United States	12	615 0.9×	658 1.3×	123 0.7×	182 1.4×	40 0.3×	19	1.0k
David M. Eisenmann United States	22	937 1.3×	1.3k 2.5×	309 1.7×	355 2.6×	112 0.9×	31	1.8k
Allison L. Abbott United States	14	425 0.6×	891 1.7×	43 0.2×	363 2.7×	38 0.3×	19	1.4k
Alessandro Puoti Switzerland	21	517 0.7×	1.3k 2.5×	93 0.5×	195 1.5×	179 1.5×	30	1.9k
Aaron M. Kershner United States	13	630 0.9×	842 1.6×	121 0.7×	89 0.7×	52 0.4×	14	1.1k

Countries citing papers authored by Cathy Savage‐Dunn

Since Specialization

Citations

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

Fields of papers citing papers by Cathy Savage‐Dunn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cathy Savage‐Dunn. 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 Cathy Savage‐Dunn. The network helps show where Cathy Savage‐Dunn may publish in the future.

Co-authorship network of co-authors of Cathy Savage‐Dunn

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

All Works

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20 of 20 papers shown

Vora, Mehul, et al.. (2025). Genome-wide analysis of Smad and Schnurri transcription factors in C. elegans demonstrates widespread interaction and a function in collagen secretion. eLife. 13. 1 indexed citations

Shapira, Michal, Barbara Pees, Daniel Kim, et al.. (2024). An Enterobacteriaceae Bloom in Aging Animals is Restrained by the Gut Microbiome. PubMed. 1(1). 20240024–20240024. 1 indexed citations

Vora, Mehul, et al.. (2024). Genome-wide analysis of Smad and Schnurri transcription factors in C. elegans demonstrates widespread interaction and a function in collagen secretion. eLife. 13. 1 indexed citations

Reich, Hannah, et al.. (2024). BMP signaling to pharyngeal muscle in the C. elegans response to a bacterial pathogen regulates anti-microbial peptide expression and pharyngeal pumping. Molecular Biology of the Cell. 35(4). ar52–ar52. 5 indexed citations

Aggad, Dina, Nicolas Brouilly, Shizue Omi, et al.. (2023). Meisosomes, folded membrane microdomains between the apical extracellular matrix and epidermis. eLife. 12. 14 indexed citations

Savage‐Dunn, Cathy, et al.. (2023). TGF-β pathways in aging and immunity: lessons from Caenorhabditis elegans. Frontiers in Genetics. 14. 1220068–1220068. 10 indexed citations

Savage‐Dunn, Cathy, et al.. (2021). Nanoscale Structure and Mechanics of Skin in a C. elegans Model of Touch Sensation. Biophysical Journal. 120(3). 234a–235a. 1 indexed citations

Rushlow, Christine, et al.. (2018). BMP Signaling Determines Body Size via Transcriptional Regulation of Collagen Genes in Caenorhabditis elegans. Genetics. 210(4). 1355–1367. 31 indexed citations

Hall, David H., et al.. (2017). Caenorhabditis elegans DBL-1/BMP Regulates Lipid Accumulation via Interaction with Insulin Signaling. G3 Genes Genomes Genetics. 8(1). 343–351. 31 indexed citations

10.

Savage‐Dunn, Cathy, et al.. (2017). Chloride intracellular channel proteins respond to heat stress in Caenorhabditis elegans. PLoS ONE. 12(9). e0184308–e0184308. 8 indexed citations

11.

Savage‐Dunn, Cathy & Richard W. Padgett. (2017). The TGF-β Family inCaenorhabditis elegans. Cold Spring Harbor Perspectives in Biology. 9(6). a022178–a022178. 54 indexed citations

12.

Fernando, Thilini R., et al.. (2011). C. elegans ADAMTS ADT-2 regulates body size by modulating TGFβ signaling and cuticle collagen organization. Developmental Biology. 352(1). 92–103. 27 indexed citations

13.

Savage‐Dunn, Cathy, et al.. (2011). Non-stringent tissue-source requirements for BMP ligand expression in regulation of body size inCaenorhabditis elegans. Genetics Research. 93(6). 427–432. 10 indexed citations

14.

Yu, Ling, et al.. (2007). Transcriptional repressor and activator activities of SMA-9 contribute differentially to BMP-related signaling outputs. Developmental Biology. 305(2). 714–725. 47 indexed citations

15.

Yu, Ling, et al.. (2007). A role for sperm in regulation of egg-laying in the Nematode C. elegans. BMC Developmental Biology. 7(1). 41–41. 20 indexed citations

16.

Savage‐Dunn, Cathy. (2005). TGF-β signaling. WormBook. 1–12. 98 indexed citations

17.

Li, Jau‐Yi, Katherine M. Gast, Xia Chen, et al.. (2004). Detection of intracellular iron by its regulatory effect. American Journal of Physiology-Cell Physiology. 287(6). C1547–C1559. 44 indexed citations

18.

Savage‐Dunn, Cathy. (2001). Targets of TGFβ-related signaling in Caenorhabditis elegans. Cytokine & Growth Factor Reviews. 12(4). 305–312. 26 indexed citations

19.

Padgett, Richard W., Cathy Savage‐Dunn, & Pradeep Kumar Das. (1997). Genetic and biochemical analysis of TGFβ signal transduction. Cytokine & Growth Factor Reviews. 8(1). 1–9. 24 indexed citations

20.

Savage‐Dunn, Cathy, et al.. (1991). Genetic aspects of microtubule biology in the nematode Caenorhabditis elegans. Cell Motility and the Cytoskeleton. 18(3). 159–163. 9 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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