Birgit Michels

1000 total citations
21 papers, 593 citations indexed

About

Birgit Michels is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Genetics. According to data from OpenAlex, Birgit Michels has authored 21 papers receiving a total of 593 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cellular and Molecular Neuroscience, 8 papers in Molecular Biology and 8 papers in Genetics. Recurrent topics in Birgit Michels's work include Neurobiology and Insect Physiology Research (12 papers), CAR-T cell therapy research (7 papers) and Insect and Arachnid Ecology and Behavior (5 papers). Birgit Michels is often cited by papers focused on Neurobiology and Insect Physiology Research (12 papers), CAR-T cell therapy research (7 papers) and Insect and Arachnid Ecology and Behavior (5 papers). Birgit Michels collaborates with scholars based in Germany, Switzerland and United Kingdom. Birgit Michels's co-authors include Bertram Gerber, Sören Diegelmann, Erich Buchner, Hiromu Tanimoto, Thomas Hendel, Kirsa Neuser, Timo Saumweber, Martin Heisenberg, Michael Schleyer and Brigitte Neuber and has published in prestigious journals such as Journal of Neuroscience, Blood and Journal of Ethnopharmacology.

In The Last Decade

Birgit Michels

21 papers receiving 582 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Birgit Michels Germany 16 369 204 151 145 140 21 593
John B. Connolly United Kingdom 10 533 1.4× 243 1.2× 426 2.8× 15 0.1× 99 0.7× 22 884
Carl Sung United States 10 338 0.9× 78 0.4× 187 1.2× 23 0.2× 41 0.3× 14 475
Nasima Mayer United States 8 268 0.7× 68 0.3× 149 1.0× 44 0.3× 51 0.4× 9 502
Brendan Mullaney United States 10 171 0.5× 295 1.4× 294 1.9× 25 0.2× 46 0.3× 12 679
Jonathan C. Radford United Kingdom 8 461 1.2× 218 1.1× 318 2.1× 15 0.1× 176 1.3× 9 784
Noëlle D. L’Étoile United States 19 338 0.9× 176 0.9× 661 4.4× 18 0.1× 60 0.4× 30 1.4k
Wonseok Son South Korea 8 393 1.1× 143 0.7× 208 1.4× 15 0.1× 79 0.6× 15 666
Bowen Deng China 12 396 1.1× 124 0.6× 186 1.2× 8 0.1× 84 0.6× 33 678
Elizabeth A. Kane United States 7 397 1.1× 178 0.9× 245 1.6× 8 0.1× 67 0.5× 7 809
Hirofumi Kunitomo Japan 21 262 0.7× 131 0.6× 651 4.3× 15 0.1× 43 0.3× 32 1.4k

Countries citing papers authored by Birgit Michels

Since Specialization
Citations

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

Fields of papers citing papers by Birgit Michels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Birgit Michels

This figure shows the co-authorship network connecting the top 25 collaborators of Birgit Michels. A scholar is included among the top collaborators of Birgit Michels 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 Birgit Michels. Birgit Michels 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.
Schubert, Maria‐Luisa, Peter Dreger, Anita Schmitt, et al.. (2024). Third-generation anti-CD19 CAR T cells for relapsed/refractory chronic lymphocytic leukemia: a phase 1/2 study. Leukemia. 38(11). 2419–2428. 18 indexed citations
2.
3.
Schubert, Maria‐Luisa, Alexander Kunz, Anita Schmitt, et al.. (2020). Assessment of CAR T Cell Frequencies in Axicabtagene Ciloleucel and Tisagenlecleucel Patients Using Duplex Quantitative PCR. Cancers. 12(10). 2820–2820. 14 indexed citations
4.
Kunz, Alexander, Ulrike Gern, Anita Schmitt, et al.. (2020). Optimized Assessment of qPCR-Based Vector Copy Numbers as a Safety Parameter for GMP-Grade CAR T Cells and Monitoring of Frequency in Patients. Molecular Therapy — Methods & Clinical Development. 17. 448–454. 28 indexed citations
5.
Michels, Birgit, et al.. (2020). Rewarding compounds identified from the medicinal plant Rhodiola rosea. Journal of Experimental Biology. 223(16). 4 indexed citations
6.
Wang, Lei, Wenjie Gong, Sanmei Wang, et al.. (2019). Improvement of in vitro potency assays by a resting step for clinical-grade chimeric antigen receptor engineered T cells. Cytotherapy. 21(5). 566–578. 17 indexed citations
7.
8.
Kahl, Evelyn, Radwa Khalil, Birgit Michels, et al.. (2019). Rhodiola rosea root extract has antipsychotic-like effects in rodent models of sensorimotor gating. Journal of Ethnopharmacology. 235. 320–328. 15 indexed citations
9.
Schubert, Maria‐Luisa, Anita Schmitt, Brigitte Neuber, et al.. (2019). Third-Generation CAR T Cells Targeting CD19 Are Associated with an Excellent Safety Profile and Might Improve Persistence of CAR T Cells in Treated Patients. Blood. 134(Supplement_1). 51–51. 42 indexed citations
10.
Michels, Birgit, Timo Saumweber, Michael Schleyer, et al.. (2017). Pavlovian Conditioning of Larval Drosophila: An Illustrated, Multilingual, Hands-On Manual for Odor-Taste Associative Learning in Maggots. Frontiers in Behavioral Neuroscience. 11. 45–45. 21 indexed citations
11.
Chen, Yi‐Chun, Birgit Michels, Timo Saumweber, et al.. (2015). Synapsin is required to “boost” memory strength for highly salient events. Learning & Memory. 23(1). 9–20. 14 indexed citations
12.
Niewalda, Thomas, et al.. (2015). Synapsin Determines Memory Strength after Punishment- and Relief-Learning. Journal of Neuroscience. 35(19). 7487–7502. 24 indexed citations
13.
Niewalda, Thomas, et al.. (2014). ‘Peer pressure’ in larval Drosophila?. Biology Open. 3(7). 575–582. 7 indexed citations
14.
Sadanandappa, Madhumala K., Beatriz Blanco-Redondo, Birgit Michels, et al.. (2013). Synapsin Function in GABA-ergic Interneurons Is Required for Short-Term Olfactory Habituation. Journal of Neuroscience. 33(42). 16576–16585. 29 indexed citations
15.
Diegelmann, Sören, Bert R. E. Klagges, Birgit Michels, Michael Schleyer, & Bertram Gerber. (2013). Maggot learning and Synapsin function. Journal of Experimental Biology. 216(6). 939–951. 47 indexed citations
16.
Saumweber, Timo, Stefan Hallermann, Sören Diegelmann, et al.. (2011). Behavioral and Synaptic Plasticity Are Impaired upon Lack of the Synaptic Protein SAP47. Journal of Neuroscience. 31(9). 3508–3518. 19 indexed citations
17.
Michels, Birgit, Yi‐Chung Chen, Timo Saumweber, et al.. (2011). Cellular site and molecular mode of synapsin action in associative learning. Learning & Memory. 18(5). 332–344. 38 indexed citations
18.
Yarali, Ayse, Markus Krischke, Birgit Michels, et al.. (2008). Genetic Distortion of the Balance between Punishment and Relief Learning in Drosophila. Journal of Neurogenetics. 23(1-2). 235–247. 36 indexed citations
19.
Michels, Birgit, et al.. (2005). A role for Synapsin in associative learning: The Drosophila larva as a study case. Learning & Memory. 12(3). 224–231. 66 indexed citations
20.
Hendel, Thomas, Birgit Michels, Kirsa Neuser, et al.. (2005). The carrot, not the stick: appetitive rather than aversive gustatory stimuli support associative olfactory learning in individually assayed Drosophila larvae. Journal of Comparative Physiology A. 191(3). 265–279. 55 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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