Håkan Steiner

6.3k total citations · 2 hit papers
40 papers, 5.2k citations indexed

About

Håkan Steiner is a scholar working on Immunology, Molecular Biology and Microbiology. According to data from OpenAlex, Håkan Steiner has authored 40 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Immunology, 15 papers in Molecular Biology and 15 papers in Microbiology. Recurrent topics in Håkan Steiner's work include Invertebrate Immune Response Mechanisms (28 papers), Antimicrobial Peptides and Activities (15 papers) and Neurobiology and Insect Physiology Research (11 papers). Håkan Steiner is often cited by papers focused on Invertebrate Immune Response Mechanisms (28 papers), Antimicrobial Peptides and Activities (15 papers) and Neurobiology and Insect Physiology Research (11 papers). Håkan Steiner collaborates with scholars based in Sweden, United States and France. Håkan Steiner's co-authors include Dan Hultmark, Hans G. Boman, Peter Mellroth, Torgny Rasmuson, Daiwu Kang, Gang Liu, Jenny Karlsson, Bengt‐Harald Jonsson, Sven Lindskog and Thomas Werner 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

Håkan Steiner

40 papers receiving 5.0k citations

Hit Papers

Insect Immunity. Purification and Properties of Three Ind... 1975 2026 1992 2009 1980 1975 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Håkan Steiner Sweden 31 3.4k 1.9k 1.9k 1.8k 903 40 5.2k
Shoichiro Kurata Japan 37 2.4k 0.7× 1.7k 0.9× 1.8k 0.9× 627 0.4× 907 1.0× 121 4.5k
Minoru Yamakawa Japan 40 2.0k 0.6× 2.2k 1.2× 1.8k 0.9× 1.4k 0.8× 602 0.7× 140 4.4k
Marie Lagueux France 29 2.1k 0.6× 1.1k 0.5× 2.0k 1.0× 703 0.4× 1.6k 1.7× 41 3.9k
Shunji Natori Japan 54 3.2k 1.0× 4.9k 2.6× 3.1k 1.6× 2.0k 1.1× 1.7k 1.8× 320 8.7k
Masaaki Ashida Japan 33 3.0k 0.9× 1.1k 0.6× 2.3k 1.2× 395 0.2× 1.4k 1.6× 51 4.2k
Ji-Hwan Ryu South Korea 32 2.5k 0.7× 1.5k 0.8× 2.4k 1.3× 275 0.2× 664 0.7× 56 5.8k
Charles Hétru France 48 5.5k 1.6× 3.7k 1.9× 5.3k 2.8× 3.8k 2.1× 2.0k 2.2× 82 10.6k
Jean‐Marc Reichhart France 47 7.9k 2.3× 3.0k 1.6× 5.4k 2.8× 2.6k 1.4× 2.2k 2.5× 76 10.5k
Ingrid Faye Sweden 38 1.9k 0.6× 1.4k 0.7× 1.7k 0.9× 899 0.5× 585 0.6× 67 3.8k
Philippe Bulet France 68 7.1k 2.1× 5.7k 3.0× 4.9k 2.5× 7.2k 4.1× 1.6k 1.8× 162 14.0k

Countries citing papers authored by Håkan Steiner

Since Specialization
Citations

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

Fields of papers citing papers by Håkan Steiner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Håkan Steiner

This figure shows the co-authorship network connecting the top 25 collaborators of Håkan Steiner. A scholar is included among the top collaborators of Håkan Steiner 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 Håkan Steiner. Håkan Steiner 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.
Lindberg, Bo Gustav, et al.. (2014). Medium from γ-irradiated Escherichia coli bacteria stimulates a unique immune response in Drosophila cells. Developmental & Comparative Immunology. 46(2). 392–400. 1 indexed citations
2.
Karlsson, Jenny, et al.. (2011). Growing Bacteria Shed Elicitors of <i>Drosophila </i>Humoral Immunity. Journal of Innate Immunity. 4(1). 111–116. 5 indexed citations
3.
Zaidman-Rémy, Anna, Mickaël Poidevin, Mireille Hervé, et al.. (2011). Drosophila Immunity: Analysis of PGRP-SB1 Expression, Enzymatic Activity and Function. PLoS ONE. 6(2). e17231–e17231. 81 indexed citations
4.
Steiner, Håkan, et al.. (2007). Peptidoglycan recognition protein LF: A negative regulator of Drosophila immunity. Insect Biochemistry and Molecular Biology. 37(12). 1309–1316. 48 indexed citations
5.
Mellroth, Peter & Håkan Steiner. (2006). PGRP-SB1: An N-acetylmuramoyl l-alanine amidase with antibacterial activity. Biochemical and Biophysical Research Communications. 350(4). 994–999. 124 indexed citations
6.
Coteur, G., Peter Mellroth, David Gillan, et al.. (2006). Peptidoglycan recognition proteins with amidase activity in early deuterostomes (Echinodermata). Developmental & Comparative Immunology. 31(8). 790–804. 44 indexed citations
7.
Kaneko, Takashi, William E. Goldman, Peter Mellroth, et al.. (2004). Monomeric and Polymeric Gram-Negative Peptidoglycan but Not Purified LPS Stimulate the Drosophila IMD Pathway. Immunity. 20(5). 637–649. 349 indexed citations
8.
Werner, Thomas, et al.. (2003). Functional Diversity of the Drosophila PGRP-LC Gene Cluster in the Response to Lipopolysaccharide and Peptidoglycan. Journal of Biological Chemistry. 278(29). 26319–26322. 157 indexed citations
9.
Karlsson, Jenny, et al.. (2003). A mammalian peptidoglycan recognition protein with N-acetylmuramoyl-l-alanine amidase activity. Biochemical and Biophysical Research Communications. 306(4). 988–994. 138 indexed citations
10.
Mellroth, Peter, Jenny Karlsson, & Håkan Steiner. (2003). A Scavenger Function for a DrosophilaPeptidoglycan Recognition Protein. Journal of Biological Chemistry. 278(9). 7059–7064. 289 indexed citations
11.
Lundström, Annika, Gang Liu, Daiwu Kang, Klavs Berzins, & Håkan Steiner. (2002). Trichoplusia ni gloverin, an inducible immune gene encoding an antibacterial insect protein. Insect Biochemistry and Molecular Biology. 32(7). 795–801. 47 indexed citations
12.
Kang, Daiwu, Annika Lundström, Gang Liu, & Håkan Steiner. (2002). An azurocidin-like protein is induced in Trichoplusia ni larval gut cells after bacterial challenge. Developmental & Comparative Immunology. 26(6). 495–503. 10 indexed citations
13.
Ekengren, Sophia, Ylva Tryselius, Mitchell S. Dushay, et al.. (2001). A humoral stress response in Drosophila. Current Biology. 11(9). 714–718. 106 indexed citations
14.
Liu, Chao, et al.. (2000). Mammalian Peptidoglycan Recognition Protein Binds Peptidoglycan with High Affinity, Is Expressed in Neutrophils, and Inhibits Bacterial Growth. Journal of Biological Chemistry. 275(32). 24490–24499. 171 indexed citations
15.
Liu, Gang, Daiwu Kang, & Håkan Steiner. (2000). Trichoplusia ni Lebocin, an Inducible Immune Gene with a Downstream Insertion Element. Biochemical and Biophysical Research Communications. 269(3). 803–807. 31 indexed citations
16.
Kang, Daiwu, Annika Lundström, & Håkan Steiner. (1996). Trichoplusia ni attacin A, a differentially displayed insect gene coding for an antibacterial protein. Gene. 174(2). 245–249. 21 indexed citations
17.
Gunne, Hans & Håkan Steiner. (1993). Efficient secretion of attacin from insect fat‐body cells requires proper processing of the prosequence. European Journal of Biochemistry. 214(1). 287–293. 15 indexed citations
18.
Gunne, Hans, et al.. (1991). Expression and post‐translational processing of preprocecropin A using a baculovirus vector. European Journal of Biochemistry. 199(2). 435–439. 25 indexed citations
20.
Steiner, Håkan. (1982). Secondary structure of the cecropins: antibacterial peptides from the moth Hyalophora cecropia. FEBS Letters. 137(2). 283–287. 115 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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