Nathan M. Young

4.8k total citations
63 papers, 3.2k citations indexed

About

Nathan M. Young is a scholar working on Genetics, Geometry and Topology and Molecular Biology. According to data from OpenAlex, Nathan M. Young has authored 63 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Genetics, 23 papers in Geometry and Topology and 21 papers in Molecular Biology. Recurrent topics in Nathan M. Young's work include Morphological variations and asymmetry (23 papers), Evolution and Paleontology Studies (13 papers) and dental development and anomalies (12 papers). Nathan M. Young is often cited by papers focused on Morphological variations and asymmetry (23 papers), Evolution and Paleontology Studies (13 papers) and dental development and anomalies (12 papers). Nathan M. Young collaborates with scholars based in United States, Canada and United Kingdom. Nathan M. Young's co-authors include Benedikt Hallgrímsson, Ralph Marcucio, Michael E. Steiper, Heather A. Jamniczky, Günter P. Wagner, Trish E. Parsons, Campbell Rolian, Julia C. Boughner, Diane Hu and Katherine E. Willmore and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Nathan M. Young

60 papers receiving 3.2k citations

Peers

Nathan M. Young

GENET

PALEO

Rui Diogo United States

Donald L. Swiderski United States

Barbara L. Lundrigan United States

Robert J. Asher United Kingdom

Charles C. Roseman United States

Andrea Cardini Italy

Graham J. Slater United States

Jean‐Christophe Auffray France

Kathleen K. Smith United States

Gabriel Marroig Brazil

Rui Diogo United States

Nathan M. Young

471 ×0.4

746 ×0.7

568 ×0.6

GENET

1.2k ×1.3

PALEO

579 ×1.3

Citations per year, relative to Nathan M. Young Nathan M. Young (= 1×) peers Rui Diogo

Countries citing papers authored by Nathan M. Young

Since Specialization

Citations

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

Fields of papers citing papers by Nathan M. Young

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan M. Young. 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 Nathan M. Young. The network helps show where Nathan M. Young may publish in the future.

Co-authorship network of co-authors of Nathan M. Young

This figure shows the co-authorship network connecting the top 25 collaborators of Nathan M. Young. A scholar is included among the top collaborators of Nathan M. Young 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 Nathan M. Young. Nathan M. Young 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

Vidal‐García, Marta, Katherine A. Brakora, Nathan M. Young, et al.. (2024). Dosage‐dependent effects of FGFR2^W290R mutation on craniofacial shape and cellular dynamics of the basicranial synchondroses. The Anatomical Record. 308(7). 1944–1971. 1 indexed citations

Young, Nathan M., et al.. (2023). A comparative approach for characterizing the relationship among morphology, range-of-motion and locomotor behaviour in the primate shoulder. Proceedings of the Royal Society B Biological Sciences. 290(2009). 20231446–20231446. 6 indexed citations

Peach, Daniel A.H., Cassandra Carroll, Suelí Maria Gomes, et al.. (2021). Nectar-dwelling microbes of common tansy are attractive to its mosquito pollinator, Culex pipiens L.. SHILAP Revista de lepidopterología. 21(1). 29–29. 23 indexed citations

Zaid, Musa, Nathan M. Young, Valentina Pedoia, et al.. (2020). Radiographic shoulder parameters and their relationship to outcomes following rotator cuff repair: a systematic review. Shoulder & Elbow. 13(4). 371–379. 3 indexed citations

Hassan, Mohamed G., et al.. (2020). Effects of Multi-Generational Soft Diet Consumption on Mouse Craniofacial Morphology. Frontiers in Physiology. 11. 783–783. 11 indexed citations

Clouthier, Allison L., Ryan T. Bicknell, Michael J. Bey, et al.. (2018). In silico modeling of glenohumeral joint variation in biomechanical function and stability. 165. 155. 1 indexed citations

Green, Rebecca M., Jennifer L. Fish, Nathan M. Young, et al.. (2017). Developmental nonlinearity drives phenotypic robustness. Nature Communications. 8(1). 1970–1970. 56 indexed citations

Young, Nathan M., Marta Linde‐Medina, John W. Fondon, Benedikt Hallgrímsson, & Ralph Marcucio. (2017). Craniofacial diversification in the domestic pigeon and the evolution of the avian skull. Nature Ecology & Evolution. 1(4). 95–95. 35 indexed citations

Young, Nathan M.. (2017). Integrating “Evo” and “Devo”: The Limb as Model Structure. Integrative and Comparative Biology. 57(6). 1293–1302. 18 indexed citations

10.

Hallgrímsson, Benedikt, Christopher J. Percival, Rebecca M. Green, et al.. (2015). Morphometrics, 3D Imaging, and Craniofacial Development. Current topics in developmental biology. 115. 561–597. 62 indexed citations

11.

Li, Xin, Nathan M. Young, Diane Hu, et al.. (2013). Quantification of shape and cell polarity reveals a novel mechanism underlying malformations resulting from related FGF mutations during facial morphogenesis. Human Molecular Genetics. 22(25). 5160–5172. 27 indexed citations

12.

Marcucio, Ralph, Nathan M. Young, Diane Hu, & Benedikt Hallgrímsson. (2011). Mechanisms that underlie co‐variation of the brain and face. genesis. 49(4). 177–189. 127 indexed citations

13.

Young, Nathan M., et al.. (2010). Quantitative analyses link modulation of sonic hedgehog signaling to continuous variation in facial growth and shape. Development. 137(20). 3405–3409. 107 indexed citations

14.

Hallgrímsson, Benedikt, Heather A. Jamniczky, Nathan M. Young, et al.. (2009). Deciphering the Palimpsest: Studying the Relationship Between Morphological Integration and Phenotypic Covariation. Evolutionary Biology. 36(4). 355–376. 325 indexed citations

15.

Brugmann, Samantha A., Kara E. Powder, Nathan M. Young, et al.. (2009). Comparative gene expression analysis of avian embryonic facial structures reveals new candidates for human craniofacial disorders. Human Molecular Genetics. 19(5). 920–930. 54 indexed citations

16.

Boughner, Julia C., et al.. (2008). Short‐faced mice and developmental interactions between the brain and the face. Journal of Anatomy. 213(6). 646–662. 52 indexed citations

17.

Young, Nathan M., et al.. (2007). Comparative morphometrics of embryonic facial morphogenesis: Implications for cleft‐lip etiology. The Anatomical Record. 290(1). 123–139. 34 indexed citations

18.

Hallgrímsson, Benedikt, et al.. (2006). Evolution of Covariance in the Mammalian Skull. Novartis Foundation symposium. 284. 164–190. 80 indexed citations

19.

Young, Nathan M.. (2006). Function, ontogeny and canalization of shape variance in the primate scapula. Journal of Anatomy. 209(5). 623–636. 86 indexed citations

20.

Young, Nathan M., Natallia Mikhalkevich, Ying Yan, Di Chen, & Wei-ping Zheng. (2005). Differential Regulation of Osteoblast Activity by Th Cell Subsets Mediated by Parathyroid Hormone and IFN-γ. The Journal of Immunology. 175(12). 8287–8295. 28 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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