Mark A. Hanson

4.7k total citations · 1 hit paper
49 papers, 2.4k citations indexed

About

Mark A. Hanson is a scholar working on Nature and Landscape Conservation, Ecology and Insect Science. According to data from OpenAlex, Mark A. Hanson has authored 49 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Nature and Landscape Conservation, 19 papers in Ecology and 19 papers in Insect Science. Recurrent topics in Mark A. Hanson's work include Invertebrate Immune Response Mechanisms (18 papers), Fish Ecology and Management Studies (18 papers) and Aquatic Ecosystems and Phytoplankton Dynamics (17 papers). Mark A. Hanson is often cited by papers focused on Invertebrate Immune Response Mechanisms (18 papers), Fish Ecology and Management Studies (18 papers) and Aquatic Ecosystems and Phytoplankton Dynamics (17 papers). Mark A. Hanson collaborates with scholars based in United States, Switzerland and United Kingdom. Mark A. Hanson's co-authors include Malcolm G. Butler, Bruno Lemaître, Kyle D. Zimmer, Shu Kondo, Martin Søndergaard, Steven Declerck, Erik Jeppesen, Marten Scheffer, G.J. van Geest and Luc De Meester and has published in prestigious journals such as Science, The Science of The Total Environment and Genetics.

In The Last Decade

Mark A. Hanson

46 papers receiving 2.3k citations

Hit Papers

The strain on scientific publishing 2024 2026 2025 2024 20 40 60

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark A. Hanson United States 27 1.1k 755 653 541 517 49 2.4k
Marta I. Sánchez Spain 27 2.0k 1.8× 884 1.2× 279 0.4× 210 0.4× 63 0.1× 79 2.9k
Thomas A. Jones United States 29 1.5k 1.4× 991 1.3× 601 0.9× 196 0.4× 86 0.2× 155 4.7k
Qiwei Wei China 27 566 0.5× 986 1.3× 148 0.2× 39 0.1× 610 1.2× 148 2.9k
Wolfgang Nentwig Switzerland 20 612 0.6× 596 0.8× 40 0.1× 704 1.3× 44 0.1× 35 2.4k
Ronald W. Davies Canada 26 1.7k 1.5× 984 1.3× 247 0.4× 107 0.2× 62 0.1× 163 2.7k
J. A. Beardmore United Kingdom 38 1.5k 1.3× 626 0.8× 281 0.4× 256 0.5× 142 0.3× 117 3.9k
Kevin G. Smith United States 26 1.6k 1.4× 1.4k 1.8× 131 0.2× 170 0.3× 52 0.1× 68 3.0k
Luisa Orsini United Kingdom 28 1.0k 0.9× 368 0.5× 603 0.9× 112 0.2× 27 0.1× 68 2.5k
Horst Kaiser South Africa 24 563 0.5× 493 0.7× 42 0.1× 37 0.1× 840 1.6× 94 2.4k
Brendan J. McAndrew United Kingdom 41 711 0.6× 1.1k 1.4× 47 0.1× 51 0.1× 1.1k 2.1× 126 5.6k

Countries citing papers authored by Mark A. Hanson

Since Specialization
Citations

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

Fields of papers citing papers by Mark A. Hanson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark A. Hanson. 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 Mark A. Hanson. The network helps show where Mark A. Hanson may publish in the future.

Co-authorship network of co-authors of Mark A. Hanson

This figure shows the co-authorship network connecting the top 25 collaborators of Mark A. Hanson. A scholar is included among the top collaborators of Mark A. Hanson 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 Mark A. Hanson. Mark A. Hanson 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.
Rapin, M, et al.. (2025). Layers of immunity: Deconstructing the Drosophila effector response. eLife. 14. 1 indexed citations
3.
Hanson, Mark A., et al.. (2025). Varying phylogenetic signal in susceptibility to four bacterial pathogens across species of Drosophilidae. Proceedings of the Royal Society B Biological Sciences. 292(2045). 20242239–20242239. 1 indexed citations
4.
Hanson, Mark A., et al.. (2024). The Drosophila immunity handbook. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 12 indexed citations
5.
Hanson, Mark A.. (2024). When the microbiome shapes the host: immune evolution implications for infectious disease. Philosophical Transactions of the Royal Society B Biological Sciences. 379(1901). 20230061–20230061. 14 indexed citations
6.
Hanson, Mark A., et al.. (2024). The strain on scientific publishing. Quantitative Science Studies. 5(4). 823–843. 68 indexed citations breakdown →
7.
Hanson, Mark A. & Bruno Lemaître. (2023). Antimicrobial peptides do not directly contribute to aging in Drosophila, but improve lifespan by preventing dysbiosis. Disease Models & Mechanisms. 16(4). 27 indexed citations
8.
Hanson, Mark A., et al.. (2023). Ecology-relevant bacteria drive the evolution of host antimicrobial peptides in Drosophila. Science. 381(6655). eadg5725–eadg5725. 50 indexed citations
9.
Hanson, Mark A., Shu Kondo, & Bruno Lemaître. (2022). Drosophila immunity: the Drosocin gene encodes two host defence peptides with pathogen-specific roles. Proceedings of the Royal Society B Biological Sciences. 289(1977). 20220773–20220773. 22 indexed citations
10.
Hanson, Mark A. & Bruno Lemaître. (2022). Repeated truncation of a modular antimicrobial peptide gene for neural context. PLoS Genetics. 18(6). e1010259–e1010259. 8 indexed citations
11.
12.
Marra, Alice, Mark A. Hanson, Shu Kondo, Berra Erkoşar, & Bruno Lemaître. (2021). Drosophila Antimicrobial Peptides and Lysozymes Regulate Gut Microbiota Composition and Abundance. mBio. 12(4). e0082421–e0082421. 99 indexed citations
13.
Hanson, Mark A., Lianne B. Cohen, Alice Marra, et al.. (2021). The Drosophila Baramicin polypeptide gene protects against fungal infection. PLoS Pathogens. 17(8). e1009846–e1009846. 40 indexed citations
14.
Dudzic, Jan P., Mark A. Hanson, Igor Iatsenko, Shu Kondo, & Bruno Lemaître. (2019). More Than Black or White: Melanization and Toll Share Regulatory Serine Proteases in Drosophila. Cell Reports. 27(4). 1050–1061.e3. 95 indexed citations
15.
Hanson, Mark A., Bruno Lemaître, & Robert L. Unckless. (2019). Dynamic Evolution of Antimicrobial Peptides Underscores Trade-Offs Between Immunity and Ecological Fitness. Frontiers in Immunology. 10. 2620–2620. 47 indexed citations
16.
Hanson, Mark A., Anna Dostálová, Camilla Ceroni, et al.. (2019). Synergy and remarkable specificity of antimicrobial peptides in vivo using a systematic knockout approach. eLife. 8. 172 indexed citations
17.
Hanson, Mark A., Phineas T. Hamilton, & Steve J. Perlman. (2016). Immune genes and divergent antimicrobial peptides in flies of the subgenus Drosophila. BMC Evolutionary Biology. 16(1). 228–228. 30 indexed citations
18.
Jacob, Donna L., et al.. (2015). Multi-Elements in Waters and Sediments of Shallow Lakes: Relationships with Water, Sediment, and Watershed Characteristics. Wetlands. 35(3). 443–457. 11 indexed citations
19.
Zimmer, Kyle D., et al.. (2013). Relative importance of phosphorus, fish biomass, and watershed land use as drivers of phytoplankton abundance in shallow lakes. The Science of The Total Environment. 466-467. 849–855. 21 indexed citations
20.
Hobbs, William O., Kyle D. Zimmer, Kevin M. Theissen, et al.. (2012). A 200‐year perspective on alternative stable state theory and lake management from a biomanipulated shallow lake. Ecological Applications. 22(5). 1483–1496. 56 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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