Daniel Kukral

885 total citations
9 papers, 265 citations indexed

About

Daniel Kukral is a scholar working on Molecular Biology, Cancer Research and Pharmacology. According to data from OpenAlex, Daniel Kukral has authored 9 papers receiving a total of 265 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Cancer Research and 2 papers in Pharmacology. Recurrent topics in Daniel Kukral's work include Angiogenesis and VEGF in Cancer (4 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cell Adhesion Molecules Research (2 papers). Daniel Kukral is often cited by papers focused on Angiogenesis and VEGF in Cancer (4 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cell Adhesion Molecules Research (2 papers). Daniel Kukral collaborates with scholars based in United States, India and Germany. Daniel Kukral's co-authors include Bala Krishnan, John T. Hunt, Joseph Fargnoli, Anne Lewin, Louis J. Lombardo, Barri Wautlet, Joel C. Barrish, Rajeev S. Bhide, Robert Jeyaseelan and Aberra Fura and has published in prestigious journals such as PLoS ONE, Clinical Cancer Research and Journal of Medicinal Chemistry.

In The Last Decade

Daniel Kukral

9 papers receiving 259 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Kukral United States 8 105 68 61 37 35 9 265
Misato Ito Japan 10 76 0.7× 165 2.4× 57 0.9× 75 2.0× 51 1.5× 35 350
Kwee Hyun Suh South Korea 9 141 1.3× 150 2.2× 69 1.1× 17 0.5× 78 2.2× 32 341
D. Barone United States 8 144 1.4× 125 1.8× 67 1.1× 31 0.8× 15 0.4× 12 312
Stacey Skala United States 8 104 1.0× 70 1.0× 48 0.8× 17 0.5× 35 1.0× 8 228
Patrícia Maciejewski United States 4 116 1.1× 43 0.6× 43 0.7× 10 0.3× 79 2.3× 9 282
Liv Johannessen United States 8 241 2.3× 152 2.2× 42 0.7× 14 0.4× 35 1.0× 19 374
Jin Shu China 9 111 1.1× 39 0.6× 25 0.4× 27 0.7× 89 2.5× 18 285
M Sharif United States 8 166 1.6× 59 0.9× 14 0.2× 38 1.0× 35 1.0× 13 311
Marlena Walls United States 8 202 1.9× 84 1.2× 51 0.8× 6 0.2× 16 0.5× 11 312
Jacob LaStant United States 4 144 1.4× 31 0.5× 24 0.4× 23 0.6× 51 1.5× 4 236

Countries citing papers authored by Daniel Kukral

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kukral

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Kukral. 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 Daniel Kukral. The network helps show where Daniel Kukral may publish in the future.

Co-authorship network of co-authors of Daniel Kukral

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

All Works

9 of 9 papers shown
1.
Tang, Haiying, Daniel Kukral, Yu-Wen Li, et al.. (2018). Mapping the central effects of (±)-ketamine and traxoprodil using pharmacological magnetic resonance imaging in awake rats. Journal of Psychopharmacology. 32(2). 146–155. 10 indexed citations
2.
Gillooly, Kathleen M., Claudine Pulicicchio, Mark A. Pattoli, et al.. (2017). Bruton's tyrosine kinase inhibitor BMS-986142 in experimental models of rheumatoid arthritis enhances efficacy of agents representing clinical standard-of-care. PLoS ONE. 12(7). e0181782–e0181782. 47 indexed citations
3.
Madireddi, Malavi T., Daniel Kukral, Anjaneya Chimalakonda, et al.. (2016). BMS-986089 is a high affinity anti-myostatin adnectin that increases muscle volume in three preclinical species. Neuromuscular Disorders. 26. S94–S95. 9 indexed citations
4.
Wong, Tai W., Francis Y. Lee, Stuart L. Emanuel, et al.. (2011). Antitumor and Antiangiogenic Activities of BMS-690514, an Inhibitor of Human EGF and VEGF Receptor Kinase Families. Clinical Cancer Research. 17(12). 4031–4041. 18 indexed citations
5.
Bhide, Rajeev S., Louis J. Lombardo, John T. Hunt, et al.. (2010). The Antiangiogenic Activity in Xenograft Models of Brivanib, a Dual Inhibitor of Vascular Endothelial Growth Factor Receptor-2 and Fibroblast Growth Factor Receptor-1 Kinases. Molecular Cancer Therapeutics. 9(2). 369–378. 52 indexed citations
6.
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8.
Kukral, Daniel, Jennifer Postelnek, Bala Krishnan, et al.. (2005). Prophylactic administration of abatacept prevents disease and bone destruction in a rat model of collagen-induced arthritis. Journal of Autoimmunity. 25(3). 165–171. 37 indexed citations
9.
Kukral, Daniel, Jennifer Postelnek, Bala Krishnan, et al.. (2005). Prophylactic administration of abatacept (CTLA4-Ig; BMS-188667) prevents disease induction and bone destruction in a rat model of collagen-induced arthritis. Arthritis Research. 7(Suppl 1). P4–P4. 6 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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