Thomas Stockner

3.8k total citations
106 papers, 2.8k citations indexed

About

Thomas Stockner is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Thomas Stockner has authored 106 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Molecular Biology, 42 papers in Cellular and Molecular Neuroscience and 25 papers in Oncology. Recurrent topics in Thomas Stockner's work include Neuroscience and Neuropharmacology Research (28 papers), Drug Transport and Resistance Mechanisms (25 papers) and Receptor Mechanisms and Signaling (24 papers). Thomas Stockner is often cited by papers focused on Neuroscience and Neuropharmacology Research (28 papers), Drug Transport and Resistance Mechanisms (25 papers) and Receptor Mechanisms and Signaling (24 papers). Thomas Stockner collaborates with scholars based in Austria, United States and Germany. Thomas Stockner's co-authors include Harald H. Sitte, Michael Freissmuth, Dániel Szöllősi, Gerhard F. Ecker, Peter Chiba, Oliver Kudlacek, D. Peter Tieleman, Walter Sandtner, Marion Holy and Narakorn Khunweeraphong and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Thomas Stockner

104 papers receiving 2.8k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Thomas Stockner 1.5k 947 613 261 205 106 2.8k
Hongwei Jin 2.2k 1.4× 231 0.2× 320 0.5× 144 0.6× 172 0.8× 222 5.5k
Kevin Beaumont 2.3k 1.5× 1.5k 1.6× 611 1.0× 43 0.2× 164 0.8× 103 5.0k
Seok‐Yong Lee 2.8k 1.8× 862 0.9× 241 0.4× 151 0.6× 1.1k 5.4× 65 4.2k
Meng Cui 2.8k 1.9× 656 0.7× 346 0.6× 78 0.3× 591 2.9× 102 5.2k
Katarzyna Kieć‐Kononowicz 2.3k 1.5× 584 0.6× 246 0.4× 167 0.6× 209 1.0× 294 4.9k
Matthias Engel 1.8k 1.2× 253 0.3× 364 0.6× 61 0.2× 472 2.3× 134 3.7k
John D. McCorvy 3.0k 2.0× 2.5k 2.7× 153 0.2× 115 0.4× 105 0.5× 71 4.9k
Erhu Cao 2.1k 1.4× 799 0.8× 498 0.8× 140 0.5× 1.8k 8.8× 27 4.5k
Satoshi Shuto 3.1k 2.1× 238 0.3× 343 0.6× 67 0.3× 173 0.8× 329 6.2k
Carlos Davio 1.3k 0.9× 302 0.3× 449 0.7× 75 0.3× 51 0.2× 117 2.8k

Countries citing papers authored by Thomas Stockner

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Stockner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Stockner

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Stockner. A scholar is included among the top collaborators of Thomas Stockner 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 Thomas Stockner. Thomas Stockner 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.
Neumann, Anna, et al.. (2025). Substrate-specific effects point to the important role of Y361 as part of the YER motif in closing the binding pocket of OCT1. Journal of Biological Chemistry. 301(4). 108318–108318.
2.
Farr, Clemens V., Ali El‐Kasaby, Walter Sandtner, et al.. (2024). Probing the Chemical Space of Guanidino-Carboxylic Acids to Identify the First Blockers of the Creatine-Transporter-1. Molecular Pharmacology. 106(6). 319–333.
3.
Gsell, Matthias A. F., et al.. (2024). PIP2 modulates TRPC3 activity via TRP helix and S4-S5 linker. Nature Communications. 15(1). 5220–5220. 7 indexed citations
4.
Scott, Kenneth R., Marco Niello, Oliver Kudlacek, et al.. (2024). Bioisosteric analogs of MDMA : Improving the pharmacological profile?. Journal of Neurochemistry. 168(9). 2022–2042. 3 indexed citations
5.
Niello, Marco, Julian Maier, Felix P. Mayer, et al.. (2024). Ligand coupling mechanism of the human serotonin transporter differentiates substrates from inhibitors. Nature Communications. 15(1). 417–417. 7 indexed citations
6.
Tiapko, Oleksandra, et al.. (2024). Deciphering the mechanism of cholesterol sensing in TRPC3 through photopharmacology. Biophysical Journal. 123(3). 393a–393a. 1 indexed citations
7.
Farr, Clemens V., Ali El‐Kasaby, Dániel Szöllősi, et al.. (2023). Probing binding and occlusion of substrate in the human creatine transporter‐1 by computation and mutagenesis. Protein Science. 33(1). e4842–e4842. 3 indexed citations
8.
Mocsár, Gábor, Thomas Stockner, László Homolya, et al.. (2023). Nucleotide binding is the critical regulator of ABCG2 conformational transitions. eLife. 12. 10 indexed citations
9.
Niello, Marco, Julian Maier, Walter Sandtner, et al.. (2023). Persistent binding at dopamine transporters determines sustained psychostimulant effects. Proceedings of the National Academy of Sciences. 120(6). e2114204120–e2114204120. 13 indexed citations
10.
Gsell, Matthias A. F., et al.. (2022). Characterization of DAG Binding to TRPC Channels by Target-Dependent cis–trans Isomerization of OptoDArG. Biomolecules. 12(6). 799–799. 8 indexed citations
11.
Tiapko, Oleksandra, et al.. (2022). Diacylglycerols interact with the L2 lipidation site in TRPC3 to induce a sensitized channel state. EMBO Reports. 23(7). e54276–e54276. 18 indexed citations
12.
Stockner, Thomas, et al.. (2021). Analysis of Sequence Divergence in Mammalian ABCGs Predicts a Structural Network of Residues That Underlies Functional Divergence. International Journal of Molecular Sciences. 22(6). 3012–3012. 4 indexed citations
13.
Das, Anand Kant, Dino Luethi, Dániel Szöllősi, et al.. (2020). SLC6 transporter oligomerization. Journal of Neurochemistry. 157(4). 919–929. 26 indexed citations
14.
Szöllősi, Dániel, Qiong Yang, Edin Muratspahić, et al.. (2020). Functional Impact of the G279S Substitution in the Adenosine A1-Receptor (A1R-G279S7.44), a Mutation Associated with Parkinson’s Disease. Molecular Pharmacology. 98(3). 250–266. 12 indexed citations
15.
Lichtenegger, Michaela, Oleksandra Tiapko, Barbora Svobodová, et al.. (2018). An optically controlled probe identifies lipid-gating fenestrations within the TRPC3 channel. Nature Chemical Biology. 14(4). 396–404. 96 indexed citations
16.
17.
Singer, Josef, Judit Fazekas, Wei Wang, et al.. (2014). Generation of a Canine Anti-EGFR (ErbB-1) Antibody for Passive Immunotherapy in Dog Cancer Patients. Molecular Cancer Therapeutics. 13(7). 1777–1790. 41 indexed citations
18.
Singer, Josef, Thomas Stockner, Diana Mechtcheriakova, et al.. (2012). Comparative oncology: ErbB-1 and ErbB-2 homologues in canine cancer are susceptible to cetuximab and trastuzumab targeting. Molecular Immunology. 50(4). 200–209. 73 indexed citations
19.
Bąk, Andrzej, et al.. (2010). MoStBioDat – Molecular and Structural Bioinformatics Database. Combinatorial Chemistry & High Throughput Screening. 13(4). 366–374. 3 indexed citations
20.
Stockner, Thomas, et al.. (2004). Direct Simulation of Transmembrane Helix Association: Role of Asparagines. Biophysical Journal. 87(3). 1650–1656. 35 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Hongwei Jin Breakdown of academic impact, for papers by Kevin Beaumont Breakdown of academic impact, for papers by Seok‐Yong Lee Breakdown of academic impact, for papers by Meng Cui Breakdown of academic impact, for papers by Katarzyna Kieć‐Kononowicz Breakdown of academic impact, for papers by Matthias Engel Breakdown of academic impact, for papers by John D. McCorvy Breakdown of academic impact, for papers by Erhu Cao Breakdown of academic impact, for papers by Satoshi Shuto Breakdown of academic impact, for papers by Carlos Davio
Rankless by CCL
2026