Michael Dolan

1.8k total citations
52 papers, 1.3k citations indexed

About

Michael Dolan is a scholar working on Molecular Biology, Virology and Immunology. According to data from OpenAlex, Michael Dolan has authored 52 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 10 papers in Virology and 10 papers in Immunology. Recurrent topics in Michael Dolan's work include HIV Research and Treatment (10 papers), RNA and protein synthesis mechanisms (7 papers) and Immune Cell Function and Interaction (7 papers). Michael Dolan is often cited by papers focused on HIV Research and Treatment (10 papers), RNA and protein synthesis mechanisms (7 papers) and Immune Cell Function and Interaction (7 papers). Michael Dolan collaborates with scholars based in United States, Canada and Netherlands. Michael Dolan's co-authors include Giulia Fabozzi, Nancy J. Sullivan, Christopher S. Nabel, Allison Kraus, Bradley R. Groveman, Byron Caughey, John R. Hassell, Brian W. Rigatti, Lara M. Taubner and Reed B. Wickner and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Blood.

In The Last Decade

Michael Dolan

48 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Dolan United States 22 673 377 274 263 175 52 1.3k
Viviana Falcón Cuba 21 563 0.8× 309 0.8× 186 0.7× 319 1.2× 76 0.4× 72 1.5k
Manjula Kalia India 20 461 0.7× 660 1.8× 295 1.1× 362 1.4× 89 0.5× 43 1.6k
Bruno Beaumelle France 23 1.0k 1.5× 222 0.6× 600 2.2× 293 1.1× 541 3.1× 61 1.9k
Takuo Mizukami Japan 18 537 0.8× 235 0.6× 422 1.5× 381 1.4× 207 1.2× 67 1.4k
Nathalie Chazal France 21 734 1.1× 635 1.7× 361 1.3× 310 1.2× 786 4.5× 41 1.7k
Marion Becker United Kingdom 19 627 0.9× 229 0.6× 485 1.8× 378 1.4× 253 1.4× 32 1.6k
Patrick P. Rose United States 17 491 0.7× 415 1.1× 227 0.8× 205 0.8× 440 2.5× 21 1.2k
Guido Hansen Germany 20 657 1.0× 285 0.8× 256 0.9× 186 0.7× 41 0.2× 42 1.7k
Pierre Lafaye France 24 928 1.4× 286 0.8× 264 1.0× 139 0.5× 70 0.4× 57 1.8k
Hidehiro Takahashi Japan 24 569 0.8× 303 0.8× 1.2k 4.4× 658 2.5× 84 0.5× 68 2.3k

Countries citing papers authored by Michael Dolan

Since Specialization
Citations

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

Fields of papers citing papers by Michael Dolan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Dolan

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Dolan. A scholar is included among the top collaborators of Michael Dolan 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 Michael Dolan. Michael Dolan 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.
2.
Dolan, Michael, et al.. (2022). CYP1B1 converts procarcinogens into genotoxins in Saccharomyces cerevisiae. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 874-875. 503440–503440. 5 indexed citations
3.
Dolan, Michael, et al.. (2020). The ASWF Takes OpenColorIO to the Next Level. 1–10. 1 indexed citations
4.
Dolan, Michael, et al.. (2017). Targeting Microtubules in Leishmania using a Combined Computational & Experimental Approach. Biophysical Journal. 112(3). 495a–495a. 1 indexed citations
5.
Morozov, Giora I., Huaying Zhao, Michael G. Mage, et al.. (2016). Interaction of TAPBPR, a tapasin homolog, with MHC-I molecules promotes peptide editing. Proceedings of the National Academy of Sciences. 113(8). E1006–15. 68 indexed citations
6.
Parra, Gabriel I., Stanislav V. Sosnovtsev, Eugenio J. Abente, et al.. (2016). Mapping and modeling of a strain-specific epitope in the Norwalk virus capsid inner shell. Virology. 492. 232–241. 10 indexed citations
7.
Cimbro, Raffaello, Francis C. Peterson, Qingbo Liu, et al.. (2016). Tyrosine-sulfated V2 peptides inhibit HIV-1 infection via coreceptor mimicry. EBioMedicine. 10. 45–54. 12 indexed citations
8.
Cimbro, Raffaello, Michael Dolan, Christina Guzzo, et al.. (2014). Tyrosine sulfation in the second variable loop (V2) of HIV-1 gp120 stabilizes V2–V3 interaction and modulates neutralization sensitivity. Proceedings of the National Academy of Sciences. 111(8). 3152–3157. 24 indexed citations
9.
Mehedi, Masfique, Thomas Hoenen, Shelly J. Robertson, et al.. (2013). Ebola Virus RNA Editing Depends on the Primary Editing Site Sequence and an Upstream Secondary Structure. PLoS Pathogens. 9(10). e1003677–e1003677. 47 indexed citations
10.
Mage, Michael G., Michael Dolan, Rui Wang, et al.. (2012). The Peptide-Receptive Transition State of MHC Class I Molecules: Insight from Structure and Molecular Dynamics. The Journal of Immunology. 189(3). 1391–1399. 55 indexed citations
11.
Dolan, Michael, James W. Noah, & Darrell E. Hurt. (2011). Comparison of Common Homology Modeling Algorithms: Application of User-Defined Alignments. Methods in molecular biology. 857. 399–414. 25 indexed citations
12.
Makiya, Michelle, Michael Dolan, Liane Agulto, Robert H. Purcell, & Zhaochun Chen. (2011). Structural basis of anthrax edema factor neutralization by a neutralizing antibody. Biochemical and Biophysical Research Communications. 417(1). 324–329. 7 indexed citations
13.
Madala, Satish K., Michael Dolan, Deepak Sharma, et al.. (2010). Mapping mouse IL‐13 binding regions using structure modeling, molecular docking, and high‐density peptide microarray analysis. Proteins Structure Function and Bioinformatics. 79(1). 282–293. 7 indexed citations
14.
Schlessman, J.L., et al.. (2008). Crystallographic Study of Hydration of an Internal Cavity in Engineered Proteins with Buried Polar or Ionizable Groups. Biophysical Journal. 94(8). 3208–3216. 29 indexed citations
15.
Dolan, Michael, et al.. (2008). Comparison of composer and ORCHESTRAR. Proteins Structure Function and Bioinformatics. 72(4). 1243–1258. 9 indexed citations
16.
Dolan, Michael, et al.. (2001). Construction and analysis of base-paired regions of the 16S rRNA in the 30S ribosomal subunit determined by constraint satisfaction molecular modelling. Journal of Molecular Graphics and Modelling. 19(6). 495–513. 3 indexed citations
17.
Dolan, Michael, et al.. (2000). Initiation factor 3-induced structural changes in the 30 s ribosomal subunit and in complexes containing tRNA f Met and mRNA 1 1Edited by D. E. Diaper. Journal of Molecular Biology. 299(3). 615–628. 30 indexed citations
18.
Noah, James W., et al.. (1999). Effects of Tetracycline and Spectinomycin on the Tertiary Structure of Ribosomal RNA in the Escherichia coli 30 S Ribosomal Subunit. Journal of Biological Chemistry. 274(23). 16576–16581. 37 indexed citations
19.
Dolan, Michael, et al.. (1999). Identity and geometry of a base triple in 16S rRNA determined by comparative sequence analysis and molecular modeling. RNA. 5(11). 1430–1439. 7 indexed citations
20.

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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