Olga Mayans

3.5k total citations
95 papers, 2.6k citations indexed

About

Olga Mayans is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Materials Chemistry. According to data from OpenAlex, Olga Mayans has authored 95 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Molecular Biology, 29 papers in Cardiology and Cardiovascular Medicine and 20 papers in Materials Chemistry. Recurrent topics in Olga Mayans's work include Cardiomyopathy and Myosin Studies (29 papers), Enzyme Structure and Function (20 papers) and RNA and protein synthesis mechanisms (15 papers). Olga Mayans is often cited by papers focused on Cardiomyopathy and Myosin Studies (29 papers), Enzyme Structure and Function (20 papers) and RNA and protein synthesis mechanisms (15 papers). Olga Mayans collaborates with scholars based in Germany, United Kingdom and United States. Olga Mayans's co-authors include Matthias Wilmanns, Richard W. Pickersgill, John A. Jenkins, Mathias Gautel, Daniel J. Rigden, Siegfried Labeit, Paul Young, Peter F. M. van der Ven, Dieter O. Fürst and Matthias Wilm and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Advanced Materials.

In The Last Decade

Olga Mayans

92 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Olga Mayans Germany 27 1.8k 687 394 366 304 95 2.6k
Carlos H.I. Ramos Brazil 32 2.6k 1.5× 300 0.4× 411 1.0× 397 1.1× 413 1.4× 145 3.5k
Perttu Permi Finland 35 2.0k 1.1× 146 0.2× 585 1.5× 488 1.3× 178 0.6× 147 3.6k
Ann H. Kwan Australia 31 1.9k 1.1× 138 0.2× 256 0.6× 293 0.8× 271 0.9× 93 2.8k
Daniel L. Purich United States 36 1.9k 1.1× 197 0.3× 1.5k 3.7× 351 1.0× 162 0.5× 110 3.5k
Dixie J. Goss United States 33 2.6k 1.5× 335 0.5× 235 0.6× 145 0.4× 631 2.1× 102 3.4k
Brian Tripet United States 28 1.7k 1.0× 452 0.7× 323 0.8× 147 0.4× 129 0.4× 81 2.7k
F. Jon Kull United States 27 2.0k 1.1× 688 1.0× 1.5k 3.9× 159 0.4× 203 0.7× 74 3.1k
Tadashi Satoh Japan 27 1.3k 0.8× 163 0.2× 464 1.2× 183 0.5× 116 0.4× 112 2.1k
William D. McCubbin Canada 27 1.3k 0.7× 330 0.5× 239 0.6× 171 0.5× 157 0.5× 74 2.0k
Paul C. Leavis United States 32 1.8k 1.0× 1.1k 1.7× 390 1.0× 245 0.7× 67 0.2× 59 3.1k

Countries citing papers authored by Olga Mayans

Since Specialization
Citations

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

Fields of papers citing papers by Olga Mayans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olga Mayans

This figure shows the co-authorship network connecting the top 25 collaborators of Olga Mayans. A scholar is included among the top collaborators of Olga Mayans 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 Olga Mayans. Olga Mayans 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.
Hartig, Jörg S., et al.. (2025). Indel-driven evolution of the canavanine tRNA-editing deacetylase enzyme CtdA. PubMed. 12. 100132–100132.
2.
Procter, James B, et al.. (2025). Protocol for sequence clustering with PaSiMap in Jalview. STAR Protocols. 6(1). 103603–103603.
3.
Matsunaga, Yohei, Hiroshi Qadota, Nasab Ghazal, et al.. (2024). Protein kinase 2 of the giant sarcomeric protein UNC-89 regulates mitochondrial morphology and function. Communications Biology. 7(1). 1342–1342. 1 indexed citations
4.
Fleming, Jennifer R., et al.. (2023). AMP-dependent phosphite dehydrogenase, a phosphorylating enzyme in dissimilatory phosphite oxidation. Proceedings of the National Academy of Sciences. 120(45). e2309743120–e2309743120. 8 indexed citations
5.
Zacharchenko, Thomas, et al.. (2023). PK1 from Drosophila obscurin is an inactive pseudokinase with scaffolding properties. Open Biology. 13(4). 220350–220350. 4 indexed citations
6.
Fleming, Jennifer R., Vasiliki Zouvelou, Francesca Andreetta, et al.. (2023). Immunological and Structural Characterization of Titin Main Immunogenic Region; I110 Domain Is the Target of Titin Antibodies in Myasthenia Gravis. Biomedicines. 11(2). 449–449. 2 indexed citations
7.
Fleming, Jennifer R., et al.. (2023). Titin UN2A Acts as a Stable, Non‐Polymorphic Scaffold in its Binding to CARP. ChemBioChem. 24(19). e202300408–e202300408.
8.
Bogomolovas, Julius, Jennifer R. Fleming, Barbara Franke, et al.. (2021). Titin kinase ubiquitination aligns autophagy receptors with mechanical signals in the sarcomere. EMBO Reports. 22(10). e48018–e48018. 31 indexed citations
9.
Matsunaga, Yohei, Barbara Franke, Hiroshi Qadota, et al.. (2021). Conformational changes in twitchin kinase in vivo revealed by FRET imaging of freely moving C. elegans. eLife. 10. 7 indexed citations
10.
Lange, Stephan, et al.. (2021). The N2A region of titin has a unique structural configuration. The Journal of General Physiology. 153(7). 11 indexed citations
11.
12.
Diederichs, Kay, et al.. (2020). Structural annotation of the conserved carbohydrate esterase vb_24B_21 from Shiga toxin-encoding bacteriophage Φ24B. Journal of Structural Biology. 212(1). 107596–107596. 2 indexed citations
13.
Thomas, Jens M. H., Felix Šimkovic, Ronan M. Keegan, et al.. (2017). Approaches toab initiomolecular replacement of α-helical transmembrane proteins. Acta Crystallographica Section D Structural Biology. 73(12). 985–996. 4 indexed citations
14.
Bogomolovas, Julius, Jennifer R. Fleming, Brian Anderson, et al.. (2016). Exploration of pathomechanisms triggered by a single-nucleotide polymorphism in titin's I-band: the cardiomyopathy-linked mutation T2580I. Open Biology. 6(9). 160114–160114. 15 indexed citations
15.
Qadota, Hiroshi, Olga Mayans, Yohei Matsunaga, et al.. (2016). The SH3 domain of UNC-89 (obscurin) interacts with paramyosin, a coiled-coil protein, inCaenorhabditis elegansmuscle. Molecular Biology of the Cell. 27(10). 1606–1620. 19 indexed citations
16.
Thomas, Jens M. H., Ronan M. Keegan, Jaclyn Bibby, et al.. (2015). Routine phasing of coiled-coil protein crystal structures withAMPLE. IUCrJ. 2(2). 198–206. 20 indexed citations
17.
Nayeem, Naushaba, Olga Mayans, & T.C. Green. (2013). Correlating efficacy and desensitization with GluK2 ligand-binding domain movements. Open Biology. 3(5). 130051–130051. 6 indexed citations
18.
Nayeem, Naushaba, Olga Mayans, & T.C. Green. (2011). Conformational Flexibility of the Ligand-Binding Domain Dimer in Kainate Receptor Gating and Desensitization. Journal of Neuroscience. 31(8). 2916–2924. 25 indexed citations
19.
Lee, Eric H., Jen Hsin, Olga Mayans, & Klaus Schulten. (2007). Secondary and Tertiary Structure Elasticity of Titin Z1Z2 and a Titin Chain Model. Biophysical Journal. 93(5). 1719–1735. 44 indexed citations
20.

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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