Nathan D. Miller

3.0k total citations
40 papers, 2.0k citations indexed

About

Nathan D. Miller is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Nathan D. Miller has authored 40 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Plant Science, 17 papers in Molecular Biology and 8 papers in Genetics. Recurrent topics in Nathan D. Miller's work include Plant Molecular Biology Research (19 papers), Plant nutrient uptake and metabolism (10 papers) and Plant Reproductive Biology (10 papers). Nathan D. Miller is often cited by papers focused on Plant Molecular Biology Research (19 papers), Plant nutrient uptake and metabolism (10 papers) and Plant Reproductive Biology (10 papers). Nathan D. Miller collaborates with scholars based in United States, Austria and South Korea. Nathan D. Miller's co-authors include Edgar P. Spalding, Gabriele B. Monshausen, Daniel R. Lewis, Guosheng Wu, Cheng Dai, Simon Gilroy, Angus Murphy, Tessa Durham Brooks, Gloria K. Muday and Shawn M. Kaeppler and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and The Journal of Cell Biology.

In The Last Decade

Nathan D. Miller

39 papers receiving 2.0k citations

Peers

Countries citing papers authored by Nathan D. Miller

Since Specialization

Citations

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

Fields of papers citing papers by Nathan D. Miller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nathan D. Miller

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

#	Work	Indexed citations
1	Separate sites of action for cry1 and phot1 blue-light receptors in the Arabidopsis hypocotyl 2024 ·Current Biology ·(unknown), Nathan D. Miller, Edgar P. Spalding	2
2	A scalable, low‐cost phenotyping strategy to assess tuber size, shape, and the colorimetric features of tuber skin and flesh in potato breeding populations 2024 ·SHILAP Revista de lepidopterología ·Max Feldman, (unknown), Nathan D. Miller, Collins Wakholi, (unknown), Arash Abbasi, (unknown), Duroy A. Navarre, (unknown), Laura M. Shannon, (unknown)	3
3	Leveraging orthology within maize and Arabidopsis QTL to identify genes affecting natural variation in gravitropism 2022 ·Proceedings of the National Academy of Sciences ·Takeshi Yoshihara, Nathan D. Miller, Fernando A. Rabanal, (unknown), Il‐Youp Kwak, Karl W. Broman, (unknown), Ivan Baxter, Brian P. Dilkes, Matthew E. Hudson, Edgar P. Spalding	3
4	A novel high-throughput hyperspectral scanner and analytical methods for predicting maize kernel composition and physical traits 2022 ·Food Chemistry ·(unknown), Nathan D. Miller, (unknown), Shawn M. Kaeppler, Natalia de León, Edgar P. Spalding	13
5	Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions 2021 ·PLANT PHYSIOLOGY ·John N. Ferguson, Samuel B. Fernandes, Brandon Monier, Nathan D. Miller, (unknown), (unknown), (unknown), Roberto Lozano, Ravi Valluru, Edward S. Buckler, Michael A. Gore, Patrick J. Brown, Edgar P. Spalding, Andrew D. B. Leakey	61
6	Using the Automated Botanical Contact Device (ABCD) to Deliver Reproducible, Intermittent Touch Stimulation to Plants 2021 ·Methods in molecular biology ·(unknown), (unknown), Nathan D. Miller, Richard Barker, (unknown), (unknown), (unknown), Sarah J. Swanson, Simon Gilroy	0
7	The complex response of free and bound amino acids to water stress during the seed setting stage in Arabidopsis 2020 ·The Plant Journal ·Abou Yobi, (unknown), Albert Batushansky, (unknown), (unknown), (unknown), (unknown), Nathan D. Miller, Thomas P. Mawhinney, Ruthie Angelovici	18
8	Characterizing introgression-by-environment interactions using maize near isogenic lines 2020 ·Theoretical and Applied Genetics ·Zhi Li, (unknown), (unknown), (unknown), Nathan D. Miller, Edgar P. Spalding, Aaron J. Lorenz, Natalia de León, Shawn M. Kaeppler, Patrick S. Schnable, Nathan M. Springer, Candice N. Hirsch	1
9	Predicting Zea mays Flowering Time, Yield, and Kernel Dimensions by Analyzing Aerial Images 2019 ·Frontiers in Plant Science ·Guosheng Wu, Nathan D. Miller, Natalia de León, Shawn M. Kaeppler, Edgar P. Spalding	23
10	Classifying cold‐stress responses of inbred maize seedlings using RGB imaging 2019 ·Plant Direct ·Tara A. Enders, (unknown), (unknown), Steven T. Callen, Malia Gehan, Nathan D. Miller, Edgar P. Spalding, Nathan M. Springer, Cory D. Hirsch	40
11	Conservation of the genome-wide recombination rate in white-footed mice 2019 ·Heredity ·(unknown), Nathan D. Miller, Bret A. Payseur	7
12	Modulation of early maize seedling performance via priming under sub-optimal temperatures 2018 ·PLoS ONE ·Gökhan Hacisalihoglu, (unknown), Nathan D. Miller, Jeffery L. Gustin, A. Mark Settles	11
13	Distribution of Endogenous NO Regulates Early Gravitropic Response and PIN2 Localization in Arabidopsis Roots 2018 ·Frontiers in Plant Science ·R París, (unknown), Magdalena Graziano, María Cecilia Terrile, Nathan D. Miller, Edgar P. Spalding, Marisa S. Otegui, Claudia A. Casalongué	23
14	TIPS: a system for automated image-based phenotyping of maize tassels 2017 ·Plant Methods ·Joseph L. Gage, Nathan D. Miller, Edgar P. Spalding, Shawn M. Kaeppler, Natalia de León	53
15	Constitutive Expression of Arabidopsis SMALL AUXIN UP RNA19 (SAUR19) in Tomato Confers Auxin-Independent Hypocotyl Elongation 2016 ·PLANT PHYSIOLOGY ·Angela Spartz, Vai S. Lor, Hong Yu Ren, Neil E. Olszewski, Nathan D. Miller, Guosheng Wu, Edgar P. Spalding, William M. Gray	83
16	The Receptor-like Kinase FERONIA Is Required for Mechanical Signal Transduction in Arabidopsis Seedlings 2014 ·Current Biology ·(unknown), Nathan D. Miller, Cheng Dai, Edgar P. Spalding, Gabriele B. Monshausen	236
17	Image analysis is driving a renaissance in growth measurement 2013 ·Current Opinion in Plant Biology ·Edgar P. Spalding, Nathan D. Miller	80
18	Separating parental environment from seed size effects on next generation growth and development in Arabidopsis 2010 ·Plant Cell & Environment ·Angela L. Elwell, (unknown), Nathan D. Miller, Edgar P. Spalding, Tessa Durham Brooks	67
19	Dynamics of auxin‐dependent Ca²⁺ and pH signaling in root growth revealed by integrating high‐resolution imaging with automated computer vision‐based analysis 2010 ·The Plant Journal ·Gabriele B. Monshausen, Nathan D. Miller, Angus Murphy, Simon Gilroy	184
20	Computer‐vision analysis of seedling responses to light and gravity 2007 ·The Plant Journal ·Nathan D. Miller, Brian M. Parks, Edgar P. Spalding	87

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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