Ashley Goss

1.7k total citations
18 papers, 1.2k citations indexed

About

Ashley Goss is a scholar working on Molecular Biology, Surgery and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Ashley Goss has authored 18 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Surgery and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Ashley Goss's work include Congenital Diaphragmatic Hernia Studies (3 papers), Atrial Fibrillation Management and Outcomes (3 papers) and Blood Coagulation and Thrombosis Mechanisms (3 papers). Ashley Goss is often cited by papers focused on Congenital Diaphragmatic Hernia Studies (3 papers), Atrial Fibrillation Management and Outcomes (3 papers) and Blood Coagulation and Thrombosis Mechanisms (3 papers). Ashley Goss collaborates with scholars based in United States, Germany and Australia. Ashley Goss's co-authors include Edward E. Morrisey, Ethan D. Cohen, Min Lü, Diane Zhou, Tadasuke Tsukiyama, Terry P. Yamaguchi, Ying Tian, Francesco J. DeMayo, Jifu Yang and John J. Lepore and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Journal of Clinical Investigation.

In The Last Decade

Ashley Goss

17 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashley Goss United States 12 731 464 382 127 99 18 1.2k
Tomonori Yoshida Japan 16 509 0.7× 194 0.4× 300 0.8× 138 1.1× 84 0.8× 60 1.2k
Carol Wong Hong Kong 14 494 0.7× 177 0.4× 253 0.7× 210 1.7× 46 0.5× 31 1.2k
Amedeo Ferlosio Italy 19 337 0.5× 284 0.6× 206 0.5× 262 2.1× 63 0.6× 57 1.1k
Katsuhiko Matsuo Japan 17 433 0.6× 151 0.3× 238 0.6× 203 1.6× 91 0.9× 23 1.2k
Christopher Major United States 10 589 0.8× 106 0.2× 201 0.5× 195 1.5× 45 0.5× 14 1.1k
Kit Man Tsang United States 10 424 0.6× 143 0.3× 152 0.4× 73 0.6× 67 0.7× 15 732
Chengqi Xu China 21 639 0.9× 130 0.3× 164 0.4× 137 1.1× 140 1.4× 78 1.2k
Hoeke A. Baarsma Netherlands 21 868 1.2× 868 1.9× 235 0.6× 112 0.9× 66 0.7× 37 1.7k
Bryce G. Johnson United States 12 579 0.8× 167 0.4× 114 0.3× 57 0.4× 68 0.7× 15 1.1k
Lukasz Stawski United States 17 454 0.6× 192 0.4× 91 0.2× 160 1.3× 86 0.9× 21 1.0k

Countries citing papers authored by Ashley Goss

Since Specialization
Citations

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

Fields of papers citing papers by Ashley Goss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashley Goss

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

All Works

18 of 18 papers shown
1.
Tangri, Navdeep, et al.. (2025). Validation of the Klinrisk Machine Learning Model for CKD Progression in a Large Representative US Population. Journal of the American Society of Nephrology. 37(2). 326–337. 1 indexed citations
2.
Hayden, Jennifer, et al.. (2021). Cardiovascular risk prediction model and stratification in patients with type 2 diabetes enrolled in a Medicare Advantage plan. Journal of Managed Care & Specialty Pharmacy. 27(11). 1579–1591. 1 indexed citations
3.
Owens, A. Phillip, Matthew J. Flick, Senad Divanovic, et al.. (2020). Thrombin promotes diet-induced obesity through fibrin-driven inflammation. UNC Libraries.
4.
Woo, Jung A., Ashley Goss, Donghwa Kim, et al.. (2019). Differential long‐term regulation of TAS2R14 by structurally distinct agonists. The FASEB Journal. 33(11). 12213–12225. 13 indexed citations
5.
Kopec, Anna K., Sherry Thornton, Joseph S. Palumbo, et al.. (2017). Thrombin promotes diet-induced obesity through fibrin-driven inflammation. Journal of Clinical Investigation. 127(8). 3152–3166. 92 indexed citations
6.
Vianello, Fabrizio, Luisa Sambado, Ashley Goss, Fabrizio Fabris, & Paolo Prandoni. (2016). Dabigatran antagonizes growth, cell‐cycle progression, migration, and endothelial tube formation induced by thrombin in breast and glioblastoma cell lines. Cancer Medicine. 5(10). 2886–2898. 27 indexed citations
7.
Angheloiu, George O., Joanne van Ryn, & Ashley Goss. (2015). Abstract 12901: Removal of Dabigatran Using Sorbent Hemadsorption. Circulation. 132(suppl_3). 2 indexed citations
8.
Alexander, Eric T., et al.. (2015). Thrombin inhibition and cyclophosphamide synergistically block tumor progression and metastasis. Cancer Biology & Therapy. 16(12). 1802–1811. 32 indexed citations
9.
Chen, Buxin, et al.. (2015). Characterization of Thrombin-Bound Dabigatran Effects on Protease-Activated Receptor-1 Expression and Signaling In Vitro. Molecular Pharmacology. 88(1). 95–105. 24 indexed citations
10.
DeNino, Walter F., et al.. (2015). The effect of ultrafiltration with cardiopulmonary bypass on the removal of dabigatran from the circulation of adult pigs. Perfusion. 31(5). 424–430. 2 indexed citations
11.
Ryn, Joanne van, Ashley Goss, Norbert Hauel, et al.. (2013). The Discovery of Dabigatran Etexilate. Frontiers in Pharmacology. 4. 12–12. 58 indexed citations
12.
13.
Durham, Amy C., Kathleen M. Stewart, Ashley Goss, et al.. (2011). Wnt/β-catenin signaling accelerates mouse lung tumorigenesis by imposing an embryonic distal progenitor phenotype on lung epithelium. Journal of Clinical Investigation. 121(5). 1935–1945. 133 indexed citations
14.
Goss, Ashley, Ying Tian, Lan Cheng, et al.. (2011). Wnt2 signaling is necessary and sufficient to activate the airway smooth muscle program in the lung by regulating myocardin/Mrtf-B and Fgf10 expression. Developmental Biology. 356(2). 541–552. 70 indexed citations
15.
Tian, Ying, Lijun Yuan, Ashley Goss, et al.. (2010). Characterization and In Vivo Pharmacological Rescue of a Wnt2-Gata6 Pathway Required for Cardiac Inflow Tract Development. Developmental Cell. 18(2). 275–287. 96 indexed citations
16.
Goss, Ashley, Ying Tian, Tadasuke Tsukiyama, et al.. (2009). Wnt2/2b and β-Catenin Signaling Are Necessary and Sufficient to Specify Lung Progenitors in the Foregut. Developmental Cell. 17(2). 290–298. 327 indexed citations
17.
Zhang, Yuzhen, Ashley Goss, Ethan D. Cohen, et al.. (2008). A Gata6-Wnt pathway required for epithelial stem cell development and airway regeneration. Nature Genetics. 40(7). 862–870. 217 indexed citations
18.
Vrana, Kent E., Jason Hipp, Ashley Goss, et al.. (2003). Nonhuman primate parthenogenetic stem cells. Proceedings of the National Academy of Sciences. 100(suppl_1). 11911–11916. 129 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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