David C. Colter

4.1k total citations · 3 hit papers
15 papers, 3.4k citations indexed

About

David C. Colter is a scholar working on Molecular Biology, Genetics and Biomedical Engineering. According to data from OpenAlex, David C. Colter has authored 15 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Genetics and 4 papers in Biomedical Engineering. Recurrent topics in David C. Colter's work include Mesenchymal stem cell research (7 papers), Pluripotent Stem Cells Research (4 papers) and Tissue Engineering and Regenerative Medicine (3 papers). David C. Colter is often cited by papers focused on Mesenchymal stem cell research (7 papers), Pluripotent Stem Cells Research (4 papers) and Tissue Engineering and Regenerative Medicine (3 papers). David C. Colter collaborates with scholars based in United States, Slovakia and Germany. David C. Colter's co-authors include Darwin J. Prockop, Carla M. DiGirolamo, Reiner Class, Ichiro Sekiya, Donald G. Phinney, Ichiro Sekiya, Elisabeth H. Javazon, Emily Schwarz, Jonathan J. Abramson and Terence G. Favero and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Biochemical and Biophysical Research Communications.

In The Last Decade

David C. Colter

15 papers receiving 3.2k citations

Hit Papers

Rapid expansion of recycling stem cells in cultures of pl... 1999 2026 2008 2017 2000 2001 1999 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David C. Colter United States 14 2.3k 1.2k 1.1k 480 472 15 3.4k
Claire Bony France 26 2.7k 1.2× 1.2k 1.0× 1.4k 1.2× 590 1.2× 624 1.3× 50 4.2k
Bruno Delorme France 24 1.6k 0.7× 783 0.7× 1.0k 1.0× 297 0.6× 517 1.1× 34 3.1k
Wonil Oh South Korea 36 2.5k 1.1× 1.3k 1.1× 1.5k 1.4× 295 0.6× 389 0.8× 86 4.4k
José J. Minguell Chile 27 2.5k 1.1× 1.4k 1.2× 1.4k 1.3× 317 0.7× 480 1.0× 81 3.8k
Robert W. Storms United States 17 2.5k 1.1× 1.5k 1.3× 1.3k 1.2× 246 0.5× 814 1.7× 32 4.0k
Benedetto Sacchetti Italy 19 1.9k 0.8× 1.0k 0.9× 1.6k 1.5× 343 0.7× 993 2.1× 33 3.9k
Anish Sen Majumdar India 27 1.4k 0.6× 1.3k 1.1× 1.4k 1.3× 445 0.9× 385 0.8× 39 3.2k
Gene Kopen United States 12 2.4k 1.0× 921 0.8× 1.2k 1.1× 228 0.5× 380 0.8× 19 3.3k
Gianluca D’Ippolito United States 19 1.2k 0.5× 718 0.6× 1.2k 1.1× 298 0.6× 343 0.7× 33 2.7k
Annemarie Moseley United States 8 3.5k 1.5× 1.6k 1.4× 1.1k 1.0× 193 0.4× 545 1.2× 16 4.2k

Countries citing papers authored by David C. Colter

Since Specialization
Citations

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

Fields of papers citing papers by David C. Colter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David C. Colter

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

All Works

15 of 15 papers shown
1.
Colter, David C., Lian‐Chao Li, Jingjie Mo, et al.. (2019). Using bispecific antibodies in forced degradation studies to analyze the structure–function relationships of symmetrically and asymmetrically modified antibodies. mAbs. 11(6). 1101–1112. 16 indexed citations
2.
Manzoli, Vita, David C. Colter, Alessia Fornoni, et al.. (2017). Engineering human renal epithelial cells for transplantation in regenerative medicine. Medical Engineering & Physics. 48(1). 3–13. 2 indexed citations
3.
Ekert, Jason E., Kjell Johnson, Brandy Strake, et al.. (2014). Three-Dimensional Lung Tumor Microenvironment Modulates Therapeutic Compound Responsiveness In Vitro – Implication for Drug Development. PLoS ONE. 9(3). e92248–e92248. 121 indexed citations
4.
Kazanecki, Christian C., David C. Colter, Anna Gosiewska, et al.. (2013). A Human In Vitro Model That Mimics the Renal Proximal Tubule. Tissue Engineering Part C Methods. 20(7). 599–609. 21 indexed citations
5.
Piera-Velázquez, Sonsoles, et al.. (2007). Regulation of the human SOX9 promoter by Sp1 and CREB. Experimental Cell Research. 313(6). 1069–1079. 75 indexed citations
6.
Colter, David C., et al.. (2005). Regulation of the human Sox9 promoter by the CCAAT-binding factor. Matrix Biology. 24(3). 185–197. 35 indexed citations
7.
Prockop, Darwin J., Ichiro Sekiya, & David C. Colter. (2001). Isolation and characterization of rapidly self-renewing stem cells from cultures of human marrow stromal cells. Cytotherapy. 3(5). 393–396. 165 indexed citations
8.
Sekiya, Ichiro, David C. Colter, & Darwin J. Prockop. (2001). BMP-6 Enhances Chondrogenesis in a Subpopulation of Human Marrow Stromal Cells. Biochemical and Biophysical Research Communications. 284(2). 411–418. 254 indexed citations
9.
Colter, David C., Ichiro Sekiya, & Darwin J. Prockop. (2001). Identification of a subpopulation of rapidly self-renewing and multipotential adult stem cells in colonies of human marrow stromal cells. Proceedings of the National Academy of Sciences. 98(14). 7841–7845. 756 indexed citations breakdown →
10.
Javazon, Elisabeth H., David C. Colter, Emily Schwarz, & Darwin J. Prockop. (2001). Rat Marrow Stromal Cells are More Sensitive to Plating Density and Expand More Rapidly from Single‐Cell‐Derived Colonies than Human Marrow Stromal Cells. Stem Cells. 19(3). 219–225. 227 indexed citations
11.
Prockop, Darwin J., S. Ausim Azizi, David C. Colter, et al.. (2000). Potential use of stem cells from bone marrow to repair the extracellular matrix and the central nervous system. Biochemical Society Transactions. 28(4). 341–345. 41 indexed citations
12.
Colter, David C., Reiner Class, Carla M. DiGirolamo, & Darwin J. Prockop. (2000). Rapid expansion of recycling stem cells in cultures of plastic-adherent cells from human bone marrow. Proceedings of the National Academy of Sciences. 97(7). 3213–3218. 779 indexed citations breakdown →
13.
DiGirolamo, Carla M., et al.. (1999). Propagation and senescence of human marrow stromal cells in culture: a simple colony‐forming assay identifies samples with the greatest potential to propagate and differentiate. British Journal of Haematology. 107(2). 275–281. 727 indexed citations breakdown →
14.
Favero, Terence G., et al.. (1998). Hypochlorous acid inhibits Ca2+-ATPase from skeletal muscle sarcoplasmic reticulum. Journal of Applied Physiology. 84(2). 425–430. 73 indexed citations
15.
Favero, Terence G., Anthony C. Zable, David C. Colter, & Jonathan J. Abramson. (1997). Lactate inhibits Ca2+-activated Ca2+-channel activity from skeletal muscle sarcoplasmic reticulum. Journal of Applied Physiology. 82(2). 447–452. 62 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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