David M. Coder

984 total citations
24 papers, 742 citations indexed

About

David M. Coder is a scholar working on Molecular Biology, Immunology and Epidemiology. According to data from OpenAlex, David M. Coder has authored 24 papers receiving a total of 742 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 6 papers in Immunology and 3 papers in Epidemiology. Recurrent topics in David M. Coder's work include T-cell and B-cell Immunology (3 papers), Algal biology and biofuel production (3 papers) and Single-cell and spatial transcriptomics (2 papers). David M. Coder is often cited by papers focused on T-cell and B-cell Immunology (3 papers), Algal biology and biofuel production (3 papers) and Single-cell and spatial transcriptomics (2 papers). David M. Coder collaborates with scholars based in United States and Canada. David M. Coder's co-authors include Lucien R. Jacobs, Simon C. Johnson, Susan K. Anderson, Kimberly A. Muczynski, Joanne R. Lupton, Alejandro Aruffo, Andrew G. Farr, J. R. Lupton, Brian E. Hall and Thaddeus C. George and has published in prestigious journals such as The Journal of Experimental Medicine, The Journal of Immunology and Journal of the American Society of Nephrology.

In The Last Decade

David M. Coder

24 papers receiving 722 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David M. Coder United States 13 276 192 102 86 79 24 742
Anyou Wang United States 13 260 0.9× 110 0.6× 64 0.6× 53 0.6× 48 0.6× 46 738
Lena Winstedt Sweden 13 279 1.0× 112 0.6× 57 0.6× 131 1.5× 79 1.0× 17 657
Serge Dumont France 16 273 1.0× 486 2.5× 226 2.2× 38 0.4× 165 2.1× 29 1.1k
Alan M. Seddon United Kingdom 19 242 0.9× 98 0.5× 42 0.4× 22 0.3× 84 1.1× 40 783
Mei Han United States 17 707 2.6× 352 1.8× 82 0.8× 14 0.2× 74 0.9× 31 1.2k
Lee Shaw Germany 17 666 2.4× 202 1.1× 71 0.7× 13 0.2× 88 1.1× 27 1.0k
Jarkko Räbinä Finland 15 536 1.9× 123 0.6× 83 0.8× 7 0.1× 103 1.3× 27 778
Giovanna Del Pozzo Italy 17 260 0.9× 327 1.7× 82 0.8× 10 0.1× 144 1.8× 52 885
Rosemarie Hunziker United States 13 345 1.3× 673 3.5× 72 0.7× 7 0.1× 66 0.8× 21 1.2k
Kiyotaka Watanabe Japan 16 261 0.9× 47 0.2× 37 0.4× 15 0.2× 32 0.4× 43 718

Countries citing papers authored by David M. Coder

Since Specialization
Citations

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

Fields of papers citing papers by David M. Coder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David M. Coder

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

All Works

20 of 20 papers shown
1.
Smith, James R., Rodica P. Bunaciu, Gudrun Reiterer, et al.. (2009). Retinoic acid induces nuclear accumulation of Raf1 during differentiation of HL-60 cells. Experimental Cell Research. 315(13). 2241–2248. 26 indexed citations
2.
Ortyn, William E., Brian E. Hall, Thaddeus C. George, et al.. (2006). Sensitivity measurement and compensation in spectral imaging. Cytometry Part A. 69A(8). 852–862. 88 indexed citations
3.
Arechiga, Adrian F., Bryan D. Bell, Claire L. Dubois, et al.. (2005). Cutting Edge: FADD Is Not Required for Antigen Receptor-Mediated NF-κB Activation. The Journal of Immunology. 175(12). 7800–7804. 35 indexed citations
4.
Muczynski, Kimberly A., et al.. (2003). Normal Human Kidney HLA-DR–Expressing Renal Microvascular Endothelial Cells. Journal of the American Society of Nephrology. 14(5). 1336–1348. 137 indexed citations
5.
Coder, David M., et al.. (2002). Multiparameter cytokine-specific affinity matrix assay for the determination of frequencies and phenotype of antigen-reactive T cells. Journal of Immunological Methods. 260(1-2). 37–42. 4 indexed citations
6.
7.
Stapleton, Ann E., et al.. (2002). Precise and rapid assessment of Escherichia coli adherence to vaginal epithelial cells by flow cytometry. Cytometry. 50(1). 31–37. 8 indexed citations
8.
Coder, David M., et al.. (1997). Concentration of RB protein in nucleus vs. cytoplasm is stable as phosphorylation of RB changes during the cell cycle and differentiation.. PubMed. 72(2). 159–65. 12 indexed citations
9.
Kahn, S. J., et al.. (1996). The major surface glycoprotein of Trypanosoma cruzi amastigotes are ligands of the human serum mannose-binding protein. Infection and Immunity. 64(7). 2649–2656. 37 indexed citations
10.
Kahn, Steven E., et al.. (1995). Trypanosoma cruzi amastigote adhesion to macrophages is facilitated by the mannose receptor.. The Journal of Experimental Medicine. 182(5). 1243–1258. 67 indexed citations
11.
Coder, David M., Doug Redelman, & Robert F. Vogt. (1994). Computing the central location of immunofluorescence distributions: Logarithmic data transformations are not always appropriate. Cytometry. 18(2). 75–78. 11 indexed citations
12.
Coder, David M., et al.. (1994). Cell subset (CS) parameter to record the identities of individual cells in flow cytometric data. Cytometry. 18(2). 95–102. 4 indexed citations
13.
Coder, David M., et al.. (1991). Increased intracellular calcium is associated with progression of HPV-18 immortalized human keratinocytes to tumorigenicity. Cell Calcium. 12(5). 343–349. 7 indexed citations
14.
Lupton, Joanne R., David M. Coder, & Lucien R. Jacobs. (1988). Long-Term Effects of Fermentable Fibers on Rat Colonic pH and Epithelial Cell Cycle. Journal of Nutrition. 118(7). 840–845. 68 indexed citations
15.
Nonomura, Arthur M. & David M. Coder. (1988). Improved Phycocatalysis of Carotene Production by Flow Cytometry and Cell Sorting. Biocatalysis. 1(4). 333–338. 11 indexed citations
16.
Coder, David M. & Lynda J. Goff. (1986). THE HOST RANGE OF THE CHLORELLAVOROUS BACTERIUM (“VAMPIROVIBRIO CHLORELLVORUS”). Journal of Phycology. 22(4). 543–546. 21 indexed citations
17.
Coder, David M.. (1986). Practical Flow Cytometry Howard Shapiro. BioScience. 36(10). 674–675. 2 indexed citations
18.
Lupton, J. R., David M. Coder, & Lucien R. Jacobs. (1985). Influence of luminal pH on rat large bowel epithelial cell cycle. American Journal of Physiology-Gastrointestinal and Liver Physiology. 249(3). G382–G388. 48 indexed citations
19.
Coder, David M.. (1985). ANOVA with SuperCalc. BioScience. 35(5). 306–307. 1 indexed citations
20.
Coder, David M. & Mortimer P. Starr. (1978). Antagonistic association of the chlorellavorus bacterium (“Bdellovibrio” chlorellavorus) withChlorella vulgaris. Current Microbiology. 1(1). 59–64. 26 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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