Ronald K. Blackman

5.4k total citations
33 papers, 2.9k citations indexed

About

Ronald K. Blackman is a scholar working on Molecular Biology, Oncology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ronald K. Blackman has authored 33 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 6 papers in Oncology and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ronald K. Blackman's work include Developmental Biology and Gene Regulation (10 papers), Heat shock proteins research (7 papers) and Neurobiology and Insect Physiology Research (4 papers). Ronald K. Blackman is often cited by papers focused on Developmental Biology and Gene Regulation (10 papers), Heat shock proteins research (7 papers) and Neurobiology and Insect Physiology Research (4 papers). Ronald K. Blackman collaborates with scholars based in United States, Canada and France. Ronald K. Blackman's co-authors include William M Gelbart, Matthew Meselson, R Grimaila, Laurel A. Raftery, Richard W. Padgett, Michele Sanicola, Yumiko Wada, Keizo Koya, James Barsoum and Christine Bulawa and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Clinical Oncology.

In The Last Decade

Ronald K. Blackman

32 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ronald K. Blackman United States 26 2.2k 398 369 351 315 33 2.9k
Michael R. Schlabach United States 19 3.1k 1.4× 340 0.9× 398 1.1× 113 0.3× 757 2.4× 27 3.8k
Kevin Blackburn United States 27 2.0k 0.9× 262 0.7× 451 1.2× 620 1.8× 412 1.3× 50 3.2k
Tsukasa Matsunaga Japan 34 3.4k 1.5× 322 0.8× 317 0.9× 648 1.8× 580 1.8× 80 4.3k
Priscilla K. Cooper United States 29 3.5k 1.6× 241 0.6× 626 1.7× 352 1.0× 499 1.6× 49 4.1k
Ottavio Fasano United States 21 3.3k 1.5× 562 1.4× 650 1.8× 166 0.5× 754 2.4× 30 4.0k
Dieter A Wolf United States 35 3.5k 1.6× 562 1.4× 378 1.0× 428 1.2× 751 2.4× 81 4.4k
Raphael Sandaltzopoulos Greece 26 2.5k 1.2× 854 2.1× 348 0.9× 325 0.9× 767 2.4× 71 3.9k
James P. Carney United States 20 4.3k 1.9× 308 0.8× 753 2.0× 386 1.1× 1.3k 4.0× 30 4.8k
Mikael Björklund United Kingdom 25 1.5k 0.7× 308 0.8× 195 0.5× 127 0.4× 407 1.3× 41 2.6k
Larry L. Deaven United States 33 3.3k 1.5× 347 0.9× 1.1k 2.9× 926 2.6× 313 1.0× 70 5.0k

Countries citing papers authored by Ronald K. Blackman

Since Specialization
Citations

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

Fields of papers citing papers by Ronald K. Blackman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronald K. Blackman. 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 Ronald K. Blackman. The network helps show where Ronald K. Blackman may publish in the future.

Co-authorship network of co-authors of Ronald K. Blackman

This figure shows the co-authorship network connecting the top 25 collaborators of Ronald K. Blackman. A scholar is included among the top collaborators of Ronald K. Blackman 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 Ronald K. Blackman. Ronald K. Blackman 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.
Blackman, Ronald K., Kahlin Cheung-Ong, Marinella Gebbia, et al.. (2012). Mitochondrial Electron Transport Is the Cellular Target of the Oncology Drug Elesclomol. PLoS ONE. 7(1). e29798–e29798. 101 indexed citations
2.
Nagai, Masazumi, Nha Huu Vo, Luisa Shin Ogawa, et al.. (2012). The oncology drug elesclomol selectively transports copper to the mitochondria to induce oxidative stress in cancer cells. Free Radical Biology and Medicine. 52(10). 2142–2150. 251 indexed citations
3.
Ying, Weiwen, Zhenjian Du, Lijun Sun, et al.. (2011). Ganetespib, a Unique Triazolone-Containing Hsp90 Inhibitor, Exhibits Potent Antitumor Activity and a Superior Safety Profile for Cancer Therapy. Molecular Cancer Therapeutics. 11(2). 475–484. 181 indexed citations
4.
Proia, David A., Kevin P. Foley, Jim Sang, et al.. (2011). Multifaceted Intervention by the Hsp90 Inhibitor Ganetespib (STA-9090) in Cancer Cells with Activated JAK/STAT Signaling. PLoS ONE. 6(4). e18552–e18552. 65 indexed citations
5.
Demetri, G. D., Michael C. Heinrich, Bartosz Chmielowski, et al.. (2011). An open-label phase II study of the Hsp90 inhibitor ganetespib (STA-9090) in patients (pts) with metastatic and/or unresectable GIST.. Journal of Clinical Oncology. 29(15_suppl). 10011–10011. 34 indexed citations
6.
7.
Pan, Jing, Deborah R. Wysong, Ronald K. Blackman, et al.. (2003). Novel Small-Molecule Inhibitors of RNA Polymerase III. Eukaryotic Cell. 2(2). 256–264. 68 indexed citations
8.
Fleming, James, et al.. (2002). Complementary whole-genome technologies reveal the cellular response to proteasome inhibition by PS-341. Proceedings of the National Academy of Sciences. 99(3). 1461–1466. 159 indexed citations
9.
Blackman, Ronald K., et al.. (1999). Cubitus interruptus is necessary but not sufficient for direct activation of a wing-specific decapentaplegic enhancer. Development. 126(16). 3669–3677. 45 indexed citations
10.
Kopp, Artyom, Ronald K. Blackman, & Ian Duncan. (1999). Wingless, Decapentaplegic and EGF Receptor signaling pathways interact to specify dorso-ventral pattern in the adult abdomen of Drosophila. Development. 126(16). 3495–3507. 55 indexed citations
11.
Twombly, Vern, Ronald K. Blackman, Hui Jin, et al.. (1996). The TGF-β signaling pathway is essential for Drosophila oogenesis. Development. 122(5). 1555–1565. 189 indexed citations
12.
Blackman, Ronald K.. (1996). Streamlined Protocol for Polytene Chromosome In Situ Hybridization. BioTechniques. 21(2). 226–230. 5 indexed citations
13.
Yu, Kweon, Mark A. Sturtevant, Brian Biehs, et al.. (1996). The Drosophila decapentaplegic and short gastrulation genes function antagonistically during adult wing vein development. Development. 122(12). 4033–4044. 79 indexed citations
14.
Finelli, Alyce L., Ting Xie, Cynthia A. Bossie, Ronald K. Blackman, & Richard W. Padgett. (1995). The tolkin gene is a tolloid/BMP-1 homologue that is essential for Drosophila development.. Genetics. 141(1). 271–281. 47 indexed citations
15.
Bergstrom, David E., et al.. (1995). Regulatory autonomy and molecular characterization of the Drosophila out at first gene.. Genetics. 139(3). 1331–1346. 26 indexed citations
16.
17.
Johnston, Daniel St, F. Michael Hoffmann, Ronald K. Blackman, et al.. (1990). Molecular organization of the decapentaplegic gene in Drosophila melanogaster.. Genes & Development. 4(7). 1114–1127. 181 indexed citations
18.
Cothren, Robert M., Rebecca Richards‐Kortum, Michael Sivak, et al.. (1990). Gastrointestinal tissue diagnosis by laser-induced fluorescence spectroscopy at endoscopy. Gastrointestinal Endoscopy. 36(2). 105–111. 244 indexed citations
19.
Blackman, Ronald K. & Matthew Meselson. (1986). Interspecific nucleotide sequence comparisons used to identify regulatory and structural features of the Drosophila hsp82 gene. Journal of Molecular Biology. 188(4). 499–515. 208 indexed citations
20.
Gelbart, William M, Vivian F. Irish, Daniel St Johnston, et al.. (1985). The Decapentaplegic Gene Complex in Drosophila melanogaster. Cold Spring Harbor Symposia on Quantitative Biology. 50(0). 119–125. 27 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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