Anna Herrmannová

1.2k total citations
19 papers, 862 citations indexed

About

Anna Herrmannová is a scholar working on Molecular Biology, Ecology and Cell Biology. According to data from OpenAlex, Anna Herrmannová has authored 19 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 1 paper in Ecology and 1 paper in Cell Biology. Recurrent topics in Anna Herrmannová's work include RNA and protein synthesis mechanisms (17 papers), RNA Research and Splicing (13 papers) and RNA modifications and cancer (12 papers). Anna Herrmannová is often cited by papers focused on RNA and protein synthesis mechanisms (17 papers), RNA Research and Splicing (13 papers) and RNA modifications and cancer (12 papers). Anna Herrmannová collaborates with scholars based in Czechia, United States and Belarus. Anna Herrmannová's co-authors include Leoš Shivaya Valášek, Susan Wagner, Lucie Cuchalová, Alan G. Hinnebusch, Stanislava Gunišová, Edit Rutkai, Vladislava Hronová, Peter J. Lukavsky, Tomáš Kouba and Jakub Zeman and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Genes & Development.

In The Last Decade

Anna Herrmannová

19 papers receiving 860 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anna Herrmannová Czechia 13 811 62 41 40 35 19 862
Stanislava Gunišová Czechia 15 837 1.0× 74 1.2× 19 0.5× 42 1.1× 44 1.3× 20 889
Sundaresan Tharun United States 12 972 1.2× 89 1.4× 38 0.9× 25 0.6× 24 0.7× 15 1.0k
Meipei She United States 7 862 1.1× 36 0.6× 36 0.9× 29 0.7× 25 0.7× 7 893
Niladri K. Sinha United States 13 625 0.8× 59 1.0× 42 1.0× 36 0.9× 40 1.1× 16 741
Wendy M. Olivas United States 14 915 1.1× 64 1.0× 47 1.1× 27 0.7× 29 0.8× 20 990
Quansheng Yang United States 11 785 1.0× 41 0.7× 16 0.4× 21 0.5× 38 1.1× 15 829
Steven Wormsley United States 9 1.0k 1.3× 91 1.5× 31 0.8× 34 0.8× 56 1.6× 10 1.1k
Meghan Zubradt United States 5 1.1k 1.3× 33 0.5× 146 3.6× 22 0.6× 42 1.2× 7 1.1k
Anna‐Lena Steckelberg United States 10 384 0.5× 62 1.0× 30 0.7× 19 0.5× 23 0.7× 13 498
Jailson Brito Querido United States 8 393 0.5× 25 0.4× 19 0.5× 24 0.6× 37 1.1× 12 454

Countries citing papers authored by Anna Herrmannová

Since Specialization
Citations

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

Fields of papers citing papers by Anna Herrmannová

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Herrmannová

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

All Works

19 of 19 papers shown
1.
Herrmannová, Anna, Jan Jelı́nek, Tomáš Vomastek, et al.. (2024). Perturbations in eIF3 subunit stoichiometry alter expression of ribosomal proteins and key components of the MAPK signaling pathways. eLife. 13. 3 indexed citations
2.
Hronová, Vladislava, Mahabub Pasha Mohammad, Anna Herrmannová, et al.. (2024). Stem-loop-induced ribosome queuing in the uORF2/ATF4 overlap fine-tunes stress-induced human ATF4 translational control. Cell Reports. 43(4). 113976–113976. 8 indexed citations
3.
Shoman, Mahmoud, Dilip Kumar, Martin Modrák, et al.. (2024). RIP-seq reveals RNAs that interact with RNA polymerase and primary sigma factors in bacteria. Nucleic Acids Research. 52(8). 4604–4626. 2 indexed citations
4.
Herrmannová, Anna, Jan Jelı́nek, Tomáš Vomastek, et al.. (2024). Perturbations in eIF3 subunit stoichiometry alter expression of ribosomal proteins and key components of the MAPK signaling pathways. eLife. 13. 5 indexed citations
5.
Wagner, Susan, Jonathan Bohlen, Anna Herrmannová, et al.. (2022). Selective footprinting of 40S and 80S ribosome subpopulations (Sel-TCP-seq) to study translation and its control. Nature Protocols. 17(10). 2139–2187. 11 indexed citations
6.
Wagner, Susan, Anna Herrmannová, Vladislava Hronová, et al.. (2020). Selective Translation Complex Profiling Reveals Staged Initiation and Co-translational Assembly of Initiation Factor Complexes. Molecular Cell. 79(4). 546–560.e7. 94 indexed citations
7.
Wagner, Susan, Petra Beznosková, Stanislava Gunišová, et al.. (2019). uS3/Rps3 controls fidelity of translation termination and programmed stop codon readthrough in co-operation with eIF3. Nucleic Acids Research. 47(21). 11326–11343. 12 indexed citations
8.
9.
Hafidh, Said, David Potěšil, Karel Müller, et al.. (2018). Dynamics of the Pollen Sequestrome Defined by Subcellular Coupled Omics. PLANT PHYSIOLOGY. 178(1). 258–282. 23 indexed citations
10.
Valášek, Leoš Shivaya, Jakub Zeman, Susan Wagner, et al.. (2017). Embraced by eIF3: structural and functional insights into the roles of eIF3 across the translation cycle. Nucleic Acids Research. 45(19). 10948–10968. 103 indexed citations
11.
Pánek, Josef, Michal Kolář, Anna Herrmannová, & Leoš Shivaya Valášek. (2016). A systematic computational analysis of the rRNA–3′ UTR sequence complementarity suggests a regulatory mechanism influencing post-termination events in metazoan translation. RNA. 22(7). 957–967. 4 indexed citations
12.
Wagner, Susan, et al.. (2016). Human eIF3b and eIF3a serve as the nucleation core for the assembly of eIF3 into two interconnected modules: the yeast-like core and the octamer. Nucleic Acids Research. 44(22). 10772–10788. 67 indexed citations
13.
Wagner, Susan, et al.. (2014). Functional and Biochemical Characterization of Human Eukaryotic Translation Initiation Factor 3 in Living Cells. Molecular and Cellular Biology. 34(16). 3041–3052. 66 indexed citations
14.
Gunišová, Stanislava, et al.. (2012). Functional Characterization of the Role of the N-terminal Domain of the c/Nip1 Subunit of Eukaryotic Initiation Factor 3 (eIF3) in AUG Recognition. Journal of Biological Chemistry. 287(34). 28420–28434. 29 indexed citations
15.
Herrmannová, Anna, D. Daujotyte, Ji‐Chun Yang, et al.. (2011). Structural analysis of an eIF3 subcomplex reveals conserved interactions required for a stable and proper translation pre-initiation complex assembly. Nucleic Acids Research. 40(5). 2294–2311. 60 indexed citations
16.
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18.
Wagner, Susan, Anna Herrmannová, Fan Zhang, et al.. (2010). The C-Terminal Region of Eukaryotic Translation Initiation Factor 3a (eIF3a) Promotes mRNA Recruitment, Scanning, and, Together with eIF3j and the eIF3b RNA Recognition Motif, Selection of AUG Start Codons. Molecular and Cellular Biology. 30(18). 4415–4434. 76 indexed citations
19.
Szamecz, Béla, Edit Rutkai, Lucie Cuchalová, et al.. (2008). eIF3a cooperates with sequences 5′ of uORF1 to promote resumption of scanning by post-termination ribosomes for reinitiation on GCN4 mRNA. Genes & Development. 22(17). 2414–2425. 111 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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