J. Gage Crump

6.3k total citations
81 papers, 4.5k citations indexed

About

J. Gage Crump is a scholar working on Molecular Biology, Cell Biology and Genetics. According to data from OpenAlex, J. Gage Crump has authored 81 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Molecular Biology, 21 papers in Cell Biology and 17 papers in Genetics. Recurrent topics in J. Gage Crump's work include Developmental Biology and Gene Regulation (35 papers), Congenital heart defects research (27 papers) and Zebrafish Biomedical Research Applications (12 papers). J. Gage Crump is often cited by papers focused on Developmental Biology and Gene Regulation (35 papers), Congenital heart defects research (27 papers) and Zebrafish Biomedical Research Applications (12 papers). J. Gage Crump collaborates with scholars based in United States, Germany and United Kingdom. J. Gage Crump's co-authors include Charles B. Kimmel, Cornelia I. Bargmann, Mary E. Swartz, Lindsey Mork, Chong Pyo Choe, Kayvan Roayaie, Masashi Kishi, Joshua R. Sanes, Y. Albert Pan and Alvaro Sagasti and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

J. Gage Crump

80 papers receiving 4.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Gage Crump United States	40	3.1k	1.0k	955	485	479	81	4.5k
Jeremy S. Dasen United States	31	3.2k 1.0×	761 0.8×	964 1.0×	395 0.8×	884 1.8×	49	4.8k
Bruce W. Draper United States	35	3.7k 1.2×	799 0.8×	1.8k 1.8×	458 0.9×	174 0.4×	49	5.4k
Filippo M. Rijli France	46	5.1k 1.6×	612 0.6×	1.7k 1.8×	429 0.9×	1.1k 2.4×	99	6.6k
Thomas Lufkin United States	46	7.9k 2.6×	559 0.6×	2.4k 2.5×	779 1.6×	649 1.4×	133	9.8k
Dario Acampora Italy	54	8.4k 2.7×	897 0.9×	2.6k 2.7×	436 0.9×	2.0k 4.1×	107	10.1k
Eva Bober Germany	36	5.1k 1.7×	425 0.4×	899 0.9×	359 0.7×	301 0.6×	64	6.3k
Juan Pedro Martı́nez-Barberá United Kingdom	46	4.1k 1.3×	378 0.4×	1.6k 1.6×	542 1.1×	544 1.1×	107	7.0k
Domingos Henrique Portugal	39	7.0k 2.2×	1.4k 1.4×	1.1k 1.1×	456 0.9×	801 1.7×	62	8.1k
Brian L. Black United States	49	8.5k 2.7×	972 1.0×	1.7k 1.8×	952 2.0×	506 1.1×	103	10.0k
Frédéric Rosa France	38	3.1k 1.0×	1.2k 1.2×	545 0.6×	462 1.0×	348 0.7×	77	4.6k

Countries citing papers authored by J. Gage Crump

Since Specialization

Citations

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

Fields of papers citing papers by J. Gage Crump

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Gage Crump. 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 J. Gage Crump. The network helps show where J. Gage Crump may publish in the future.

Co-authorship network of co-authors of J. Gage Crump

This figure shows the co-authorship network connecting the top 25 collaborators of J. Gage Crump. A scholar is included among the top collaborators of J. Gage Crump 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 J. Gage Crump. J. Gage Crump 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

Lasser, Micaela, Ya‐Wen Chen, Christian Hochstim, et al.. (2025). Repurposing of a gill gene regulatory program for outer-ear evolution. Nature. 639(8055). 682–690. 5 indexed citations

Nguyen, John D., Juan Llamas, Tuo Shi, et al.. (2023). DNA methylation in the mouse cochlea promotes maturation of supporting cells and contributes to the failure of hair cell regeneration. Proceedings of the National Academy of Sciences. 120(33). e2300839120–e2300839120. 15 indexed citations

Tseng, Kuo-Chang, et al.. (2023). Ligament injury in adult zebrafish triggers ECM remodeling and cell dedifferentiation for scar-free regeneration. npj Regenerative Medicine. 8(1). 51–51. 9 indexed citations

Barske, Lindsey, Jared C. Talbot, D’Juan T. Farmer, et al.. (2023). Nuclear receptor Nr5a2 promotes diverse connective tissue fates in the jaw. Developmental Cell. 58(6). 461–473.e7. 5 indexed citations

Fábián, Péter, et al.. (2022). Gill developmental program in the teleost mandibular arch. eLife. 11. 7 indexed citations

Balsbaugh, Jeremy L., Isaac L. Moss, Julien Bertrand, et al.. (2022). Notch signaling enhances bone regeneration in the zebrafish mandible. Development. 149(5). 17 indexed citations

Perens, Elliot A., et al.. (2021). osr1 couples intermediate mesoderm cell fate with temporal dynamics of vessel progenitor cell differentiation. Development. 148(15). 9 indexed citations

Farmer, D’Juan T., Hana Mlčochová, Yan Zhou, et al.. (2021). The developing mouse coronal suture at single-cell resolution. Nature Communications. 12(1). 4797–4797. 52 indexed citations

Ting, Man-Chun, D’Juan T. Farmer, Jinzhi He, et al.. (2021). Embryonic requirements forTcf12in the development of the mouse coronal suture. Development. 149(1). 8 indexed citations

10.

Liu, Ren, et al.. (2020). Tetraspanin18 regulates angiogenesis through VEGFR2 and Notch pathways. Biology Open. 10(2). 13 indexed citations

11.

Roelofs, Anke J., Karolina Kania, Fraser L. Collins, et al.. (2020). Identification of the skeletal progenitor cells forming osteophytes in osteoarthritis. Annals of the Rheumatic Diseases. 79(12). 1625–1634. 66 indexed citations

12.

Barske, Lindsey, Péter Fábián, Dávid Jandzík, et al.. (2020). Evolution of vertebrate gill covers via shifts in an ancient Pou3f3 enhancer. Proceedings of the National Academy of Sciences. 117(40). 24876–24884. 17 indexed citations

13.

Barske, Lindsey, et al.. (2019). Nr2f-dependent allocation of ventricular cardiomyocyte and pharyngeal muscle progenitors. PLoS Genetics. 15(2). e1007962–e1007962. 20 indexed citations

14.

Vakhshori, Venus, et al.. (2019). Sox9+ messenger cells orchestrate large-scale skeletal regeneration in the mammalian rib. eLife. 8. 47 indexed citations

15.

Barske, Lindsey, et al.. (2018). Essential Role of Nr2f Nuclear Receptors in Patterning the Vertebrate Upper Jaw. Developmental Cell. 44(3). 337–347.e5. 41 indexed citations

16.

Askary, Amjad, Pengfei Xu, Lindsey Barske, et al.. (2017). Genome-wide analysis of facial skeletal regionalization in zebrafish. Development. 144(16). 2994–3005. 37 indexed citations

17.

Patterson, Michaela, Lindsey Barske, Ben Van Handel, et al.. (2017). Frequency of mononuclear diploid cardiomyocytes underlies natural variation in heart regeneration. Nature Genetics. 49(9). 1346–1353. 241 indexed citations

18.

Zhang, Danhua, Keith P. Gates, Lindsey Barske, et al.. (2017). Endoderm Jagged induces liver and pancreas duct lineage in zebrafish. Nature Communications. 8(1). 769–769. 26 indexed citations

19.

Choe, Chong Pyo, Andrés Collazo, Le A. Trinh, et al.. (2013). Wnt-Dependent Epithelial Transitions Drive Pharyngeal Pouch Formation. Developmental Cell. 24(3). 296–309. 66 indexed citations

20.

Kishi, Masashi, Y. Albert Pan, J. Gage Crump, & Joshua R. Sanes. (2005). Mammalian SAD Kinases Are Required for Neuronal Polarization. Science. 307(5711). 929–932. 263 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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