Donald H. Dean

9.1k total citations · 2 hit papers
111 papers, 7.0k citations indexed

About

Donald H. Dean is a scholar working on Molecular Biology, Insect Science and Plant Science. According to data from OpenAlex, Donald H. Dean has authored 111 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Molecular Biology, 71 papers in Insect Science and 21 papers in Plant Science. Recurrent topics in Donald H. Dean's work include Insect Resistance and Genetics (84 papers), Insect and Pesticide Research (65 papers) and Entomopathogenic Microorganisms in Pest Control (34 papers). Donald H. Dean is often cited by papers focused on Insect Resistance and Genetics (84 papers), Insect and Pesticide Research (65 papers) and Entomopathogenic Microorganisms in Pest Control (34 papers). Donald H. Dean collaborates with scholars based in United States, Colombia and Malaysia. Donald H. Dean's co-authors include Daniel R. Zeigler, Neil Crickmore, Jerald S. Feitelson, Jeroen Van Rie, E. Schnepf, Didier Lereclus, J A Baum, Francis Rajamohan, April Curtiss and Mi Kyong Lee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Donald H. Dean

109 papers receiving 6.6k citations

Hit Papers

Bacillus thuringiensis and Its Pesticidal Crystal Proteins 1998 2026 2007 2016 1998 1998 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Donald H. Dean United States 41 6.6k 5.1k 2.5k 435 390 111 7.0k
Neil Crickmore United Kingdom 35 7.1k 1.1× 5.8k 1.1× 3.1k 1.2× 346 0.8× 197 0.5× 164 7.7k
Jeroen Van Rie Belgium 35 6.9k 1.0× 5.5k 1.1× 3.6k 1.5× 216 0.5× 135 0.3× 55 7.5k
Mário Soberón Mexico 50 8.7k 1.3× 6.8k 1.3× 3.9k 1.6× 277 0.6× 248 0.6× 205 9.6k
Michael J. Adang United States 50 5.7k 0.9× 4.3k 0.8× 2.8k 1.1× 167 0.4× 88 0.2× 101 6.1k
Alejandra Bravo Mexico 56 10.1k 1.5× 8.4k 1.6× 4.5k 1.8× 223 0.5× 198 0.5× 235 11.0k
Raymond J. St. Leger United States 64 6.1k 0.9× 8.8k 1.7× 4.8k 1.9× 1.5k 3.5× 535 1.4× 143 11.3k
Karl Gordon Australia 38 2.7k 0.4× 1.9k 0.4× 2.0k 0.8× 469 1.1× 372 1.0× 97 4.3k
Daniel R. Zeigler United States 18 3.8k 0.6× 2.5k 0.5× 1.5k 0.6× 439 1.0× 497 1.3× 27 4.3k
Walter R. Terra Brazil 49 4.7k 0.7× 4.9k 0.9× 2.0k 0.8× 1.1k 2.5× 425 1.1× 208 7.9k
Nemat O. Keyhani United States 43 3.7k 0.6× 4.2k 0.8× 2.1k 0.8× 623 1.4× 337 0.9× 165 6.3k

Countries citing papers authored by Donald H. Dean

Since Specialization
Citations

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

Fields of papers citing papers by Donald H. Dean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Donald H. Dean

This figure shows the co-authorship network connecting the top 25 collaborators of Donald H. Dean. A scholar is included among the top collaborators of Donald H. Dean 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 H. Dean. Donald H. Dean 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
2.
Hussain, Syed-Rehan A., et al.. (2010). Preferential Protection of Domains II and III of Bacillus thuringiensis Cry1Aa Toxin by Brush Border Membrane Vesicles. SHILAP Revista de lepidopterología. 1 indexed citations
3.
Abdullah, Mohd Amir F., Algimantas P. Valaitis, & Donald H. Dean. (2006). Identification of a Bacillus thuringiensis Cry11Ba toxin-binding aminopeptidase from the mosquito, Anopheles quadrimaculatus. BMC Biochemistry. 7(1). 16–16. 48 indexed citations
4.
Dean, Donald H., et al.. (2006). Redesigning Bacillus thuringiensis Cry1Aa toxin into a mosquito toxin. Protein Engineering Design and Selection. 19(3). 107–111. 29 indexed citations
5.
Dean, Donald H., et al.. (2005). A new species of frog (Ranidae, Rhacophorinae, Philautus) from the rainforest canopy in the Western Ghats, India. Current Science. 88(1). 175–178. 17 indexed citations
6.
Dean, Donald H., et al.. (2004). Structural implication of the induced immune response by Bacillus thuringiensis Cry proteins: role of the N-terminal region. Molecular Immunology. 41(12). 1177–1183. 24 indexed citations
9.
Karim, Shahid, Sheikh Riazuddin, & Donald H. Dean. (1999). Interaction of Bacillus thuringiensis δ-endotoxins with Midgut Brush Border Membrane Vesicles of Helicoverpa armigera. Journal of Asia-Pacific Entomology. 2(2). 153–162. 2 indexed citations
10.
Schnepf, E., Neil Crickmore, Jeroen Van Rie, et al.. (1998). Bacillus thuringiensis and Its Pesticidal Crystal Proteins. HAL (Le Centre pour la Communication Scientifique Directe). 142 indexed citations
11.
Dean, Donald H., et al.. (1996). Inconsistencies in Determining Bacillus thuringiensis Toxin Binding Sites Relationship by Comparing Competition Assays with Ligand Blotting. Biochemical and Biophysical Research Communications. 220(3). 575–580. 30 indexed citations
12.
Valaitis, Algimantas P., Mi Kyong Lee, Francis Rajamohan, & Donald H. Dean. (1995). Brush border membrane aminopeptidase-n in the midgut of the gypsy moth serves as the receptor for the CryIA(c) δ-endotoxin of Bacillus thuringiensis. Insect Biochemistry and Molecular Biology. 25(10). 1143–1151. 102 indexed citations
13.
Patel, Smita S., et al.. (1995). Irreversible Binding Kinetics of Bacillus thuringiensis CryIA δ-Endotoxins to Gypsy Moth Brush Border Membrane Vesicles Is Directly Correlated to Toxicity. Journal of Biological Chemistry. 270(42). 24719–24724. 74 indexed citations
14.
Dean, Donald H., et al.. (1994). Intracellular Proteolysis and Limited Diversity of the Bacillus thuringiensis CryIA Family of the Insecticidal Crystal Proteins. Biochemical and Biophysical Research Communications. 201(2). 788–794. 7 indexed citations
15.
Dean, Donald H., et al.. (1993). Suppression of protein structure destabilizing mutations in Bacillus thuringiensis .delta.-endotoxins by second site mutations. Biochemistry. 32(4). 1040–1046. 9 indexed citations
16.
Pang, Sheng‐Zhi, Stephanie M. Oberhaus, Jeanette L. Rasmussen, et al.. (1992). Expression of a gene encoding a scorpion insectotoxin peptide in yeast, bacteria and plants. Gene. 116(2). 165–172. 33 indexed citations
17.
Milne, R.E., et al.. (1992). Location of a Bombyx mori receptor binding region on a Bacillus thuringiensis delta-endotoxin.. Journal of Biological Chemistry. 267(5). 3115–3121. 162 indexed citations
18.
Pfister, Robert M., et al.. (1990). Hyperexpression of a Bacillus thuringiensis delta-endotoxin-encoding gene in Escherichia coli: properties of the product. Gene. 93(1). 49–54. 63 indexed citations
19.
Dean, Donald H., et al.. (1981). A GENETIC ENGINEERING MANIFESTO FOR THE GENUS BACILLUS. Annals of the New York Academy of Sciences. 369(1). 23–32. 5 indexed citations
20.
Dean, Donald H., et al.. (1974). Low-frequency specialized transduction with Bacillus subtilis bacteriophage ∅105. Virology. 62(2). 393–403. 14 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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