Alex Tek

767 total citations
10 papers, 519 citations indexed

About

Alex Tek is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Alex Tek has authored 10 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 1 paper in Cellular and Molecular Neuroscience and 1 paper in Cardiology and Cardiovascular Medicine. Recurrent topics in Alex Tek's work include Protein Structure and Dynamics (5 papers), RNA modifications and cancer (2 papers) and Lipid Membrane Structure and Behavior (2 papers). Alex Tek is often cited by papers focused on Protein Structure and Dynamics (5 papers), RNA modifications and cancer (2 papers) and Lipid Membrane Structure and Behavior (2 papers). Alex Tek collaborates with scholars based in France, United Kingdom and United States. Alex Tek's co-authors include Marc Baaden, Matthieu Chavent, Zhihan Lv, Charly Empereur‐mot, Mark S.P. Sansom, Daniel L. Parton, Leonardo Darré, Sergio Pantano, Pierre Tufféry and Tristan Cragnolini and has published in prestigious journals such as Chemical Society Reviews, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Alex Tek

10 papers receiving 503 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alex Tek France	8	291	77	73	66	53	10	519
Nicolas Férey France	10	135 0.5×	60 0.8×	5 0.1×	26 0.4×	9 0.2×	30	280
Xinqi Fan China	16	565 1.9×	114 1.5×	4 0.1×	20 0.3×	5 0.1×	41	972
Norbert Lindow Germany	14	251 0.9×	202 2.6×	2 0.0×	42 0.6×	9 0.2×	22	557
Michael B. O’Connor United Kingdom	10	115 0.4×	77 1.0×	8 0.1×	46 0.7×	1 0.0×	13	433
Helen M. Deeks United Kingdom	7	95 0.3×	73 0.9×	9 0.1×	29 0.4×	1 0.0×	7	345
Björn Sommer Germany	13	338 1.2×	119 1.5×	1 0.0×	18 0.3×	19 0.4×	60	611
Clemens Wagner Switzerland	23	684 2.4×	42 0.5×		177 2.7×	36 0.7×	44	1.1k
Jan Stühmer Germany	8	104 0.4×	72 0.9×		24 0.4×	30 0.6×	10	385
Yina Wang China	11	117 0.4×	55 0.7×	3 0.0×	14 0.2×	6 0.1×	52	535
Július Parulek Norway	12	185 0.6×	264 3.4×	2 0.0×	34 0.5×	4 0.1×	26	467

Countries citing papers authored by Alex Tek

Since Specialization

Citations

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

Fields of papers citing papers by Alex Tek

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alex Tek

This figure shows the co-authorship network connecting the top 25 collaborators of Alex Tek. A scholar is included among the top collaborators of Alex Tek 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 Alex Tek. Alex Tek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Caulfield, Thomas R., et al.. (2019). Molecular Dynamics Simulations Suggest a Non-Doublet Decoding Model of −1 Frameshifting by tRNASer3. Biomolecules. 9(11). 745–745. 7 indexed citations

Tek, Alex, А.A. Коростелев, & Samuel Coulbourn Flores. (2015). MMB-GUI: a fast morphing method demonstrates a possible ribosomal tRNA translocation trajectory. Nucleic Acids Research. 44(1). 95–105. 7 indexed citations

Sterpone, Fabio, Simone Melchionna, Pierre Tufféry, et al.. (2014). The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems. Chemical Society Reviews. 43(13). 4871–4893. 133 indexed citations

Férey, Nicolas, Mirjam Czjzek, Élisabeth Le Rumeur, et al.. (2014). Innovative interactive flexible docking method for multi-scale reconstruction elucidates dystrophin molecular assembly. Faraday Discussions. 169. 45–62. 18 indexed citations

Tek, Alex, Leonardo Darré, Peter J. Bond, et al.. (2013). A Zoom on Membrane Fusion through Coarse-Grained, Atomistic and Hybrid Molecular Dynamics of SNARE Proteins. Biophysical Journal. 104(2). 32a–32a. 1 indexed citations

Lv, Zhihan, et al.. (2013). Game On, Science - How Video Game Technology May Help Biologists Tackle Visualization Challenges. PLoS ONE. 8(3). e57990–e57990. 187 indexed citations

Parton, Daniel L., Alex Tek, Marc Baaden, & Mark S.P. Sansom. (2013). Formation of Raft-Like Assemblies within Clusters of Influenza Hemagglutinin Observed by MD Simulations. PLoS Computational Biology. 9(4). e1003034–e1003034. 47 indexed citations

Darré, Leonardo, Alex Tek, Marc Baaden, & Sergio Pantano. (2012). Mixing Atomistic and Coarse Grain Solvation Models for MD Simulations: Let WT4 Handle the Bulk. Journal of Chemical Theory and Computation. 8(10). 3880–3894. 41 indexed citations

Chavent, Matthieu, et al.. (2011). GPU‐accelerated atom and dynamic bond visualization using hyperballs: A unified algorithm for balls, sticks, and hyperboloids. Journal of Computational Chemistry. 32(13). 2924–2935. 43 indexed citations

10.

Férey, Nicolas, Julien Nelson, C. Martín, et al.. (2009). Multisensory VR interaction for protein-docking in the CoRSAIRe project. Virtual Reality. 13(4). 273–293. 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.

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