Sebastian Pechmann

2.9k total citations
25 papers, 2.1k citations indexed

About

Sebastian Pechmann is a scholar working on Molecular Biology, Cell Biology and Materials Chemistry. According to data from OpenAlex, Sebastian Pechmann has authored 25 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 3 papers in Cell Biology and 3 papers in Materials Chemistry. Recurrent topics in Sebastian Pechmann's work include Protein Structure and Dynamics (9 papers), RNA and protein synthesis mechanisms (9 papers) and Heat shock proteins research (8 papers). Sebastian Pechmann is often cited by papers focused on Protein Structure and Dynamics (9 papers), RNA and protein synthesis mechanisms (9 papers) and Heat shock proteins research (8 papers). Sebastian Pechmann collaborates with scholars based in United States, Canada and United Kingdom. Sebastian Pechmann's co-authors include Judith Frydman, Michele Vendruscolo, Gian Gaetano Tartaglia, Felix Willmund, Christopher M. Dobson, Justin W. Chartron, Marta del Álamo, Véronique Albanèse, Emmanuel D. Levy and Junmin Peng and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Sebastian Pechmann

22 papers receiving 2.0k citations

Peers

Sebastian Pechmann

GENET

IMMUN

Lisa D. Cabrita United Kingdom

Svetlana Dokudovskaya France

Bálint Mészáros Hungary

Rita Pancsa Hungary

Gábor Erdős Hungary

Katja M. Arndt Germany

Jan P. Erzberger United States

Juli D. Klemm United States

Yugong Cheng United States

Hans‐Joachim Schönfeld Switzerland

Lisa D. Cabrita United Kingdom

Sebastian Pechmann

1.6k ×0.9

220 ×0.6

325 ×1.1

285 ×1.1

GENET

141 ×1.1

IMMUN

Citations per year, relative to Sebastian Pechmann Sebastian Pechmann (= 1×) peers Lisa D. Cabrita

Countries citing papers authored by Sebastian Pechmann

Since Specialization

Citations

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

Fields of papers citing papers by Sebastian Pechmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sebastian Pechmann

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

All Works

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20 of 20 papers shown

Pechmann, Sebastian. (2024). Single-cell expression predicts neuron-specific protein homeostasis networks. Open Biology. 14(1). 230386–230386. 3 indexed citations

Pechmann, Sebastian. (2024). Heterogeneous folding landscapes and predetermined breaking points within a protein family. Protein Science. 33(12). e5205–e5205. 1 indexed citations

Pechmann, Sebastian, et al.. (2021). Inferring translational heterogeneity from Saccharomyces cerevisiae ribosome profiling. FEBS Journal. 288(15). 4541–4559. 3 indexed citations

Reiter, Taylor, Louis Gendron, Rachel Montpetit, et al.. (2020). Altered rRNA processing disrupts nuclear RNA homeostasis via competition for the poly(A)-binding protein Nab2. Nucleic Acids Research. 48(20). 11675–11694. 11 indexed citations

Pechmann, Sebastian. (2020). Programmed Trade-offs in Protein Folding Networks. Structure. 28(12). 1361–1375.e4. 5 indexed citations

Pechmann, Sebastian, et al.. (2019). Pervasive convergent evolution and extreme phenotypes define chaperone requirements of protein homeostasis. Proceedings of the National Academy of Sciences. 116(40). 20009–20014. 10 indexed citations

Kurata, Hiroyuki, et al.. (2019). Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation. BMC Bioinformatics. 20(1). 734–734. 2 indexed citations

Geller, Ron, Sebastian Pechmann, Ashley Acevedo, Raul Andino, & Judith Frydman. (2018). Hsp90 shapes protein and RNA evolution to balance trade-offs between protein stability and aggregation. Nature Communications. 9(1). 1781–1781. 56 indexed citations

Pechmann, Sebastian, Justin W. Chartron, & Judith Frydman. (2014). Local slowdown of translation by nonoptimal codons promotes nascent-chain recognition by SRP in vivo. Nature Structural & Molecular Biology. 21(12). 1100–1105. 173 indexed citations

10.

Pechmann, Sebastian, et al.. (2013). Principles of Cotranslational Ubiquitination and Quality Control at the Ribosome. Molecular Cell. 50(3). 379–393. 167 indexed citations

11.

Willmund, Felix, Marta del Álamo, Sebastian Pechmann, et al.. (2013). The Cotranslational Function of Ribosome-Associated Hsp70 in Eukaryotic Protein Homeostasis. Cell. 152(1-2). 196–209. 212 indexed citations

12.

Pechmann, Sebastian, Felix Willmund, & Judith Frydman. (2013). The Ribosome as a Hub for Protein Quality Control. Molecular Cell. 49(3). 411–421. 206 indexed citations

13.

Leitner, Alexander, Łukasz A. Joachimiak, Andreas Bracher, et al.. (2012). The Molecular Architecture of the Eukaryotic Chaperonin TRiC/CCT. Structure. 20(5). 814–825. 235 indexed citations

14.

Pechmann, Sebastian & Judith Frydman. (2012). Evolutionary conservation of codon optimality reveals hidden signatures of cotranslational folding. Nature Structural & Molecular Biology. 20(2). 237–243. 357 indexed citations

15.

Álamo, Marta del, Daniel J. Hogan, Sebastian Pechmann, et al.. (2011). Defining the Specificity of Cotranslationally Acting Chaperones by Systematic Analysis of mRNAs Associated with Ribosome-Nascent Chain Complexes. PLoS Biology. 9(7). e1001100–e1001100. 115 indexed citations

16.

Pechmann, Sebastian & Michele Vendruscolo. (2010). Derivation of a solubility condition for proteins from an analysis of the competition between folding and aggregation. Molecular BioSystems. 6(12). 2490–2497. 7 indexed citations

17.

Tartaglia, Gian Gaetano, Sebastian Pechmann, Christopher M. Dobson, & Michele Vendruscolo. (2009). A Relationship between mRNA Expression Levels and Protein Solubility in E. coli. Journal of Molecular Biology. 388(2). 381–389. 52 indexed citations

18.

Pechmann, Sebastian, Emmanuel D. Levy, Gian Gaetano Tartaglia, & Michele Vendruscolo. (2009). Physicochemical principles that regulate the competition between functional and dysfunctional association of proteins. Proceedings of the National Academy of Sciences. 106(25). 10159–10164. 132 indexed citations

19.

Pechmann, Sebastian, Emmanuel D. Levy, Gian Gaetano Tartaglia, & Michele Vendruscolo. (2008). Competition between protein aggregation and protein complex formation. BMC Bioinformatics. 9(S10). 3 indexed citations

20.

Tartaglia, Gian Gaetano, Sebastian Pechmann, Christopher M. Dobson, & Michele Vendruscolo. (2007). Life on the edge: a link between gene expression levels and aggregation rates of human proteins. Trends in Biochemical Sciences. 32(5). 204–206. 230 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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