Håvard Jenssen

10.5k total citations · 2 hit papers
135 papers, 8.4k citations indexed

About

Håvard Jenssen is a scholar working on Microbiology, Molecular Biology and Immunology. According to data from OpenAlex, Håvard Jenssen has authored 135 papers receiving a total of 8.4k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Microbiology, 65 papers in Molecular Biology and 29 papers in Immunology. Recurrent topics in Håvard Jenssen's work include Antimicrobial Peptides and Activities (70 papers), Biochemical and Structural Characterization (34 papers) and Chemical Synthesis and Analysis (17 papers). Håvard Jenssen is often cited by papers focused on Antimicrobial Peptides and Activities (70 papers), Biochemical and Structural Characterization (34 papers) and Chemical Synthesis and Analysis (17 papers). Håvard Jenssen collaborates with scholars based in Denmark, Canada and Germany. Håvard Jenssen's co-authors include Robert E. W. Hancock, Pamela Hamill, Rebecca Hancock, Biljana Mojsoska, Christopher D. Fjell, Jason Kindrachuk, Tore Jarl Gutteberg, Artem Cherkasov, Kai Hilpert and Jeanette H. Andersen and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Håvard Jenssen

132 papers receiving 8.2k citations

Hit Papers

Peptide Antimicrobial Agents 2006 2026 2012 2019 2006 2020 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
Håvard Jenssen Denmark 47 4.9k 4.7k 1.3k 952 755 135 8.4k
Wuyuan Lu United States 54 4.3k 0.9× 5.2k 1.1× 2.2k 1.7× 1.2k 1.3× 473 0.6× 169 9.0k
Peter H. Nibbering Netherlands 54 2.6k 0.5× 2.7k 0.6× 1.7k 1.3× 515 0.5× 388 0.5× 175 8.1k
André J. Ouellette United States 52 5.0k 1.0× 5.0k 1.1× 3.0k 2.3× 737 0.8× 1.4k 1.8× 141 9.9k
Gill Diamond United States 41 4.7k 1.0× 3.0k 0.6× 3.1k 2.4× 467 0.5× 427 0.6× 93 7.6k
Guðmundur H. Guðmundsson Sweden 51 5.9k 1.2× 4.2k 0.9× 3.9k 3.0× 316 0.3× 568 0.8× 121 10.1k
Renato Gennaro Italy 52 5.8k 1.2× 4.8k 1.0× 2.8k 2.2× 585 0.6× 526 0.7× 114 8.6k
Donald J. Davidson United Kingdom 45 4.0k 0.8× 2.8k 0.6× 3.0k 2.4× 383 0.4× 311 0.4× 92 7.8k
Evan F. Haney Canada 32 4.1k 0.9× 3.8k 0.8× 1.0k 0.8× 676 0.7× 496 0.7× 57 5.7k
Kai Hilpert Germany 31 3.8k 0.8× 4.3k 0.9× 730 0.6× 1.5k 1.6× 1.1k 1.4× 71 8.4k
Guangshun Wang United States 47 6.4k 1.3× 6.0k 1.3× 1.6k 1.3× 683 0.7× 701 0.9× 131 8.8k

Countries citing papers authored by Håvard Jenssen

Since Specialization
Citations

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

Fields of papers citing papers by Håvard Jenssen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Håvard Jenssen

This figure shows the co-authorship network connecting the top 25 collaborators of Håvard Jenssen. A scholar is included among the top collaborators of Håvard Jenssen 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 Håvard Jenssen. Håvard Jenssen 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.
Chakraborty, Sudip, Renxun Chen, Dennis Palms, et al.. (2024). The effect of immobilisation strategies on the ability of peptoids to reduce the adhesion of P. aeruginosa strains to contact lenses. Experimental Eye Research. 250. 110149–110149. 3 indexed citations
3.
4.
Lauritsen, Frants R., et al.. (2023). MIMS as a Low-Impact Tool to Identify Pathogens in Water. Water. 15(1). 184–184. 3 indexed citations
5.
Nielsen, Josefine Eilsø, Morgan A. Alford, Natalia Molchanova, et al.. (2022). Self-Assembly of Antimicrobial Peptoids Impacts Their Biological Effects on ESKAPE Bacterial Pathogens. ACS Infectious Diseases. 8(3). 533–545. 61 indexed citations
6.
Petković, Marija, et al.. (2021). Immunomodulatory Properties of Host Defence Peptides in Skin Wound Healing. Biomolecules. 11(7). 952–952. 42 indexed citations
7.
Pedersen, Martin Schou, Sarah Mollerup, Lone Nielsen, et al.. (2019). Genome Sequence of an Unknown Subtype of Hepatitis C Virus Genotype 6: Another Piece for the Taxonomic Puzzle. Microbiology Resource Announcements. 8(42). 3 indexed citations
8.
Moura, João, Anja E. Sørensen, Ermelindo C. Leal, et al.. (2019). microRNA-155 inhibition restores Fibroblast Growth Factor 7 expression in diabetic skin and decreases wound inflammation. Scientific Reports. 9(1). 5836–5836. 66 indexed citations
9.
Abdel-Hamid, Mahmoud, Ehab Romeih, Ali Osman, et al.. (2019). Camel milk whey hydrolysate inhibits growth and biofilm formation of Pseudomonas aeruginosa PAO1 and methicillin-resistant Staphylococcus aureus. Food Control. 111. 107056–107056. 45 indexed citations
10.
Pedersen, Martin Schou, Ulrik Fahnøe, T. A. Hansen, et al.. (2018). A near full-length open reading frame next generation sequencing assay for genotyping and identification of resistance-associated variants in hepatitis C virus. Journal of Clinical Virology. 105. 49–56. 8 indexed citations
11.
Løbner‐Olesen, Anders, et al.. (2018). LL‐37 fragments have antimicrobial activity against Staphylococcus epidermidis biofilms and wound healing potential in HaCaT cell line. Journal of Peptide Science. 24(7). e3080–e3080. 44 indexed citations
12.
Mojsoska, Biljana, et al.. (2017). Peptoids successfully inhibit the growth of gram negative E. coli causing substantial membrane damage. Scientific Reports. 7(1). 42332–42332. 76 indexed citations
13.
Wieczorek, Michał W., Håvard Jenssen, Jason Kindrachuk, et al.. (2010). Structural Studies of An Immune Modulating and Direct Antimicrobial Peptide. Biophysical Journal. 98(3). 84a–84a. 1 indexed citations
14.
Nijnik, Anastasia, Laurence Madera, Shuhua Ma, et al.. (2010). Synthetic Cationic Peptide IDR-1002 Provides Protection against Bacterial Infections through Chemokine Induction and Enhanced Leukocyte Recruitment. The Journal of Immunology. 184(5). 2539–2550. 176 indexed citations
15.
Jenssen, Håvard & Stein Ivar Aspmo. (2008). Serum Stability of Peptides. Methods in molecular biology. 494. 177–186. 98 indexed citations
16.
Jenssen, Håvard, et al.. (2008). Inhibition of HSV cell-to-cell spread by lactoferrin and lactoferricin. Antiviral Research. 79(3). 192–198. 51 indexed citations
17.
Jenssen, Håvard, Pamela Hamill, & Robert E. W. Hancock. (2006). Peptide Antimicrobial Agents. Clinical Microbiology Reviews. 19(3). 491–511. 2005 indexed citations breakdown →
18.
Samuelsen, Ørjan, Hanne H. Haukland, Håvard Jenssen, et al.. (2005). Induced resistance to the antimicrobial peptide lactoferricin B in Staphylococcus aureus. FEBS Letters. 579(16). 3421–3426. 32 indexed citations
20.
Seyfarth, M, et al.. (1978). [Course of cellular immunity in urologic neoplasms].. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 71(10). 743–6. 1 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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