Jana Haase

2.2k total citations · 1 hit paper
26 papers, 1.7k citations indexed

About

Jana Haase is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Ecology. According to data from OpenAlex, Jana Haase has authored 26 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 9 papers in Cellular and Molecular Neuroscience and 5 papers in Ecology. Recurrent topics in Jana Haase's work include Receptor Mechanisms and Signaling (9 papers), Neuroscience and Neuropharmacology Research (6 papers) and Bacteriophages and microbial interactions (5 papers). Jana Haase is often cited by papers focused on Receptor Mechanisms and Signaling (9 papers), Neuroscience and Neuropharmacology Research (6 papers) and Bacteriophages and microbial interactions (5 papers). Jana Haase collaborates with scholars based in Ireland, Germany and United Kingdom. Jana Haase's co-authors include Erich Lanka, Francesca Magnani, D. Clive Williams, Eric J. Brown, Ammi Grahn, Dennis H. Bamford, Christopher G. Tate, John Wain, Julian Parkhill and Gordon Dougan and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Applied and Environmental Microbiology.

In The Last Decade

Jana Haase

26 papers receiving 1.6k citations

Hit Papers

Simultaneous assay of every Salmonella Typhi gene using o... 2009 2026 2014 2020 2009 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Simultaneous assay of every Salmonella Typhi gene using one million transposon mutants
    2009 468 citations Gemma C. Langridge, Minh‐Duy Phan et al. Genome Research profile →

Peers

Jana Haase
Alejandro Aballay United States
Harvey J. Whitfield United States
Suguru Okuda Japan
Michail H. Karavolos United Kingdom
Brittany D. Needham United States
Andrew Makoff United Kingdom
Yves Millet France
David Moranta Spain
Alessio Soggiù Italy
Chie Kohchi Japan
Alejandro Aballay United States
Jana Haase
Citations per year, relative to Jana Haase Jana Haase (= 1×) peers Alejandro Aballay

Countries citing papers authored by Jana Haase

Since Specialization
Citations

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

Fields of papers citing papers by Jana Haase

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jana Haase

This figure shows the co-authorship network connecting the top 25 collaborators of Jana Haase. A scholar is included among the top collaborators of Jana Haase 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 Jana Haase. Jana Haase 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
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Brown, Eric J., Leilani L. Santos, Martina Gogarty, et al.. (2018). TNFα-dependent anhedonia and upregulation of hippocampal serotonin transporter activity in a mouse model of collagen-induced arthritis. Neuropharmacology. 137. 211–220. 14 indexed citations
3.
Haase, Jana, Heidi Kaastrup Müller, Agnieszka Münster‐Wandowski, et al.. (2017). Serotonin Transporter Associated Protein Complexes Are Enriched in Synaptic Vesicle Proteins and Proteins Involved in Energy Metabolism and Ion Homeostasis. ACS Chemical Neuroscience. 8(5). 1101–1116. 15 indexed citations
4.
Hollmann, Jürgen, et al.. (2016). Analytische Neubestimmung der Zuckergehalte von Roggenmahlerzeugnissen. 784–785. 1 indexed citations
5.
Haase, Jana & Eric J. Brown. (2014). Integrating the monoamine, neurotrophin and cytokine hypotheses of depression — A central role for the serotonin transporter?. Pharmacology & Therapeutics. 147. 1–11. 129 indexed citations
6.
Campos‐Torres, Antonio, et al.. (2013). The Pro-inflammatory Cytokine TNF-α Regulates the Activity and Expression of the Serotonin Transporter (SERT) in Astrocytes. Neurochemical Research. 38(4). 694–704. 100 indexed citations
7.
Haase, Jana, et al.. (2013). The ubiquitous nature of L isteria monocytogenes clones: a large‐scale M ultilocus S equence T yping study. Environmental Microbiology. 16(2). 405–416. 119 indexed citations
8.
Haase, Jana, Derek Brown, François‐Xavier Weill, et al.. (2012). Population Genetic Structure of 4,12:a:− Salmonella enterica Strains from Harbor Porpoises. Applied and Environmental Microbiology. 78(24). 8829–8833. 5 indexed citations
9.
Haase, Jana, et al.. (2012). Transforming Microbial Genotyping: A Robotic Pipeline for Genotyping Bacterial Strains. PLoS ONE. 7(10). e48022–e48022. 15 indexed citations
10.
Haase, Jana, Ronan A. Murphy, Kingshuk Roy Choudhury, & Mark Achtman. (2011). Revival of Seeliger's historical ‘Special Listeria Culture Collection’. Environmental Microbiology. 13(12). 3163–3171. 13 indexed citations
11.
Fjorback, Anja W., Heidi Kaastrup Müller, Jana Haase, Merete K. Raarup, & Ove Wiborg. (2011). Modulation of the dopamine transporter by interaction with Secretory Carrier Membrane Protein 2. Biochemical and Biophysical Research Communications. 406(2). 165–170. 16 indexed citations
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Langridge, Gemma C., Minh‐Duy Phan, Daniel J. Turner, et al.. (2009). Simultaneous assay of every Salmonella Typhi gene using one million transposon mutants. Genome Research. 19(12). 2308–2316. 468 indexed citations breakdown →
15.
Müller, Heidi Kaastrup, Ove Wiborg, & Jana Haase. (2006). Subcellular Redistribution of the Serotonin Transporter by Secretory Carrier Membrane Protein 2. Journal of Biological Chemistry. 281(39). 28901–28909. 67 indexed citations
16.
Magnani, Francesca, Christopher G. Tate, Samantha Wynne, D. Clive Williams, & Jana Haase. (2004). Partitioning of the Serotonin Transporter into Lipid Microdomains Modulates Transport of Serotonin. Journal of Biological Chemistry. 279(37). 38770–38778. 126 indexed citations
17.
Tate, Christopher G., Jana Haase, Cara Baker, et al.. (2003). Comparison of seven different heterologous protein expression systems for the production of the serotonin transporter. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1610(1). 141–153. 109 indexed citations
18.
Haase, Jana, et al.. (2001). Regulation of the serotonin transporter by interacting proteins. Biochemical Society Transactions. 29(6). 722–722. 25 indexed citations
19.
Haase, Jana, et al.. (2001). Regulation of the serotonin transporter by interacting proteins. Biochemical Society Transactions. 29(6). 722–728. 87 indexed citations
20.
Haase, Jana, Rudi Lurz, Ammi Grahn, Dennis H. Bamford, & Erich Lanka. (1995). Bacterial conjugation mediated by plasmid RP4: RSF1010 mobilization, donor-specific phage propagation, and pilus production require the same Tra2 core components of a proposed DNA transport complex. Journal of Bacteriology. 177(16). 4779–4791. 109 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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