Donald C. Miller

3.1k total citations
49 papers, 1.1k citations indexed

About

Donald C. Miller is a scholar working on Genetics, Immunology and Molecular Biology. According to data from OpenAlex, Donald C. Miller has authored 49 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Genetics, 16 papers in Immunology and 12 papers in Molecular Biology. Recurrent topics in Donald C. Miller's work include Genetic and phenotypic traits in livestock (12 papers), Reproductive Physiology in Livestock (8 papers) and T-cell and B-cell Immunology (8 papers). Donald C. Miller is often cited by papers focused on Genetic and phenotypic traits in livestock (12 papers), Reproductive Physiology in Livestock (8 papers) and T-cell and B-cell Immunology (8 papers). Donald C. Miller collaborates with scholars based in United States, United Kingdom and Germany. Donald C. Miller's co-authors include Douglas F. Antczak, Andrew G. Clark, Xu Wang, Rebecca M. Harman, Samantha A. Brooks, Jennifer M. Cassano, Bettina Wagner, Margaret M. Brosnahan, T.L. Lear and Rebecca L. Tallmadge and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nature Genetics.

In The Last Decade

Donald C. Miller

47 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Donald C. Miller United States	19	344	330	285	132	131	49	1.1k
Renée Laufer Amorim Brazil	26	545 1.6×	307 0.9×	222 0.8×	142 1.1×	93 0.7×	176	1.9k
Katrien Smits Belgium	20	352 1.0×	211 0.6×	153 0.5×	240 1.8×	99 0.8×	88	1.1k
Teresa Collins Australia	23	523 1.5×	534 1.6×	196 0.7×	67 0.5×	67 0.5×	78	2.1k
Jan Govaere Belgium	17	164 0.5×	110 0.3×	89 0.3×	238 1.8×	144 1.1×	87	896
F. Crémonesi Italy	28	625 1.8×	206 0.6×	222 0.8×	270 2.0×	69 0.5×	121	2.2k
Liliana Tatarczuch Australia	19	831 2.4×	334 1.0×	529 1.9×	81 0.6×	47 0.4×	36	2.3k
Karl Klisch Germany	18	275 0.8×	293 0.9×	241 0.8×	401 3.0×	19 0.1×	44	914
Misa Hosoe Japan	21	382 1.1×	330 1.0×	274 1.0×	348 2.6×	14 0.1×	59	1.2k
Fernanda da Cruz Landim‐Alvarenga Brazil	20	318 0.9×	188 0.6×	43 0.2×	277 2.1×	34 0.3×	123	1.6k
Phelipe Oliveira Favaron Brazil	15	171 0.5×	113 0.3×	102 0.4×	124 0.9×	27 0.2×	96	818

Countries citing papers authored by Donald C. Miller

Since Specialization

Citations

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

Fields of papers citing papers by Donald C. Miller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Donald C. Miller

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

Miller, Donald C. & Jennifer J. Doering. (2023). Process of Maintaining Self in Individuals Living With Systemic Sclerosis: A Grounded Theory Study of American Women. Western Journal of Nursing Research. 46(1). 26–35.

Jevit, Matthew, Nandina Paria, Pranab Jyoti Das, et al.. (2023). Trio-binning of a hinny refines the comparative organization of the horse and donkey X chromosomes and reveals novel species-specific features. Scientific Reports. 13(1). 3 indexed citations

Wang, Zhong, Alexandra G. Chivu, Lauren A. Choate, et al.. (2022). Prediction of histone post-translational modification patterns based on nascent transcription data. Nature Genetics. 54(3). 295–305. 55 indexed citations

Cosgrove, Elissa J., Florencia Schlamp, Heather M. Holl, et al.. (2020). Genome Diversity and the Origin of the Arabian Horse. Scientific Reports. 10(1). 9702–9702. 61 indexed citations

Miller, Donald C., et al.. (2019). MHC haplotype diversity in Icelandic horses determined by polymorphic microsatellites. Genes and Immunity. 20(8). 660–670. 17 indexed citations

Miller, Donald C.. (2018). Coming of Age in Popular Culture. 1 indexed citations

Ballingall, Keith T., Ronald E. Bontrop, Shirley A. Ellis, et al.. (2018). Comparative MHC nomenclature: report from the ISAG/IUIS-VIC committee 2018. Immunogenetics. 70(10). 625–632. 21 indexed citations

Nergadze, Solomon G., Francesca M. Piras, Riccardo Gamba, et al.. (2018). Birth, evolution, and transmission of satellite-free mammalian centromeric domains. Genome Research. 28(6). 789–799. 56 indexed citations

Moradi-Shahrbabak, Mohammad, et al.. (2017). MHC haplotype diversity in Persian Arabian horses determined using polymorphic microsatellites. Immunogenetics. 70(5). 305–315. 14 indexed citations

10.

Bergmann, Tobias, Erin Moore, John Sidney, et al.. (2017). Peptide-binding motifs of two common equine class I MHC molecules in Thoroughbred horses. Immunogenetics. 69(5). 351–358. 1 indexed citations

11.

Brosnahan, Margaret M., et al.. (2016). Ectopic Trophoblast Allografts in the Horse Resist Destruction by Secondary Immune Responses. Biology of Reproduction. 95(6). 135–135. 3 indexed citations

12.

Bergmann, Tobias, Carrie Moore, John Sidney, et al.. (2015). The common equine class I molecule Eqca-1*00101 (ELA-A3.1) is characterized by narrow peptide binding and T cell epitope repertoires. Immunogenetics. 67(11-12). 675–689. 5 indexed citations

13.

Wang, Xu, Donald C. Miller, Andrew G. Clark, & Douglas F. Antczak. (2012). Random X inactivation in the mule and horse placenta. Genome Research. 22(10). 1855–1863. 36 indexed citations

14.

Noronha, Leela E., et al.. (2012). Molecular evidence for natural killer-like cells in equine endometrial cups. Placenta. 33(5). 379–386. 22 indexed citations

15.

Mestre, Amanda M. de, David Hanlon, Hollis N. Erb, et al.. (2011). Functions of ectopically transplanted invasive horse trophoblast. Reproduction. 141(6). 849–856. 13 indexed citations

16.

Mestre, Amanda M. de, et al.. (2008). Glial Cells Missing Homologue 1 Is Induced in Differentiating Equine Chorionic Girdle Trophoblast Cells1. Biology of Reproduction. 80(2). 227–234. 24 indexed citations

17.

Tallmadge, Rebecca L., Donald C. Miller, Douglas F. Antczak, et al.. (2003). An ordered BAC contig map of the equine major histocompatibility complex. Cytogenetic and Genome Research. 102(1-4). 189–195. 62 indexed citations

18.

Miller, Donald C., et al.. (1973). First, They Learn to Read.. Science and Children.

19.

Miller, Donald C.. (1969). Knowledge of the scientific process attained by prospective elementary school teachers /. OhioLink ETD Center (Ohio Library and Information Network). 1 indexed citations

20.

Miller, Donald C.. (1951). SALES-TAX PROGRESSIVITY ATTRIBUTABLE TO A FOOD EXEMPTION. National Tax Journal. 4(2). 148–159. 1 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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