Martin Schröder

8.5k total citations · 5 hit papers
29 papers, 6.8k citations indexed

About

Martin Schröder is a scholar working on Cell Biology, Molecular Biology and Epidemiology. According to data from OpenAlex, Martin Schröder has authored 29 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cell Biology, 18 papers in Molecular Biology and 10 papers in Epidemiology. Recurrent topics in Martin Schröder's work include Endoplasmic Reticulum Stress and Disease (20 papers), Autophagy in Disease and Therapy (10 papers) and Fungal and yeast genetics research (7 papers). Martin Schröder is often cited by papers focused on Endoplasmic Reticulum Stress and Disease (20 papers), Autophagy in Disease and Therapy (10 papers) and Fungal and yeast genetics research (7 papers). Martin Schröder collaborates with scholars based in United Kingdom, United States and Germany. Martin Schröder's co-authors include Randal J. Kaufman, Chuan Yin Liu, Erich Kombrink, Klaus Hahlbrock, Kyung‐Ho Lee, Xiaohua Shen, Donalyn Scheuner, Stacey Arnold, Vipul M. Parmar and Kezhong Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Chemical Society Reviews and Journal of Biological Chemistry.

In The Last Decade

Martin Schröder

29 papers receiving 6.7k citations

Hit Papers

THE MAMMALIAN UNFOLDED PR... 2002 2026 2010 2018 2005 2004 2007 2002 2021 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Schröder United Kingdom 22 4.1k 3.4k 2.0k 831 677 29 6.8k
Chi Young Yun United States 19 3.7k 0.9× 3.6k 1.1× 1.7k 0.9× 654 0.8× 620 0.9× 31 6.2k
Hideki Yanagi Japan 39 5.2k 1.3× 5.5k 1.6× 2.2k 1.1× 801 1.0× 720 1.1× 67 8.4k
Shengyun Fang United States 43 2.5k 0.6× 5.9k 1.7× 1.7k 0.9× 453 0.5× 835 1.2× 107 8.6k
Takao Iwawaki Japan 41 3.3k 0.8× 2.6k 0.8× 1.9k 0.9× 981 1.2× 1.0k 1.5× 118 6.2k
Maria Hatzoglou United States 50 2.1k 0.5× 5.4k 1.6× 1.1k 0.6× 556 0.7× 613 0.9× 114 7.9k
D. Thomas Rutkowski United States 26 4.0k 1.0× 2.7k 0.8× 2.2k 1.1× 1.1k 1.3× 526 0.8× 49 6.0k
Michael Boyce United States 26 1.9k 0.5× 4.9k 1.4× 1.5k 0.8× 504 0.6× 1.3k 1.9× 51 7.2k
Isabel Novoa Spain 20 7.3k 1.8× 6.5k 1.9× 3.5k 1.8× 1.4k 1.7× 1.1k 1.6× 26 11.0k
Anne Bertolotti United Kingdom 29 7.0k 1.7× 6.2k 1.8× 3.6k 1.8× 1.4k 1.6× 918 1.4× 44 11.0k
Axel H. Schönthal United States 54 1.7k 0.4× 4.6k 1.3× 1.2k 0.6× 325 0.4× 701 1.0× 170 8.1k

Countries citing papers authored by Martin Schröder

Since Specialization
Citations

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

Fields of papers citing papers by Martin Schröder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Schröder

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Schröder. A scholar is included among the top collaborators of Martin Schröder 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 Martin Schröder. Martin Schröder 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.
Paton, Adrienne W., et al.. (2020). Endoplasmic reticulum stress causes insulin resistance by inhibiting delivery of newly synthesized insulin receptors to the cell surface. Molecular Biology of the Cell. 31(23). 2597–2629. 42 indexed citations
2.
Šesták, Sergej, et al.. (2017). Bypass of Activation Loop Phosphorylation by Aspartate 836 in Activation of the Endoribonuclease Activity of Ire1. Molecular and Cellular Biology. 37(16). 13 indexed citations
3.
Suwara, Monika, et al.. (2016). An initial phase of JNK activation inhibits cell death early in the endoplasmic reticulum stress response. Journal of Cell Science. 129(12). 2317–2328. 71 indexed citations
5.
Skipsey, Mark, et al.. (2013). 5′-Deoxy-5′-Hydrazinylguanosine as an Initiator of T7 Rna Polymerase-Catalyzed Transcriptions for the Preparation of Labeling-Ready RNAs. Nucleosides Nucleotides & Nucleic Acids. 32(12). 670–681. 5 indexed citations
6.
Parmar, Vipul M. & Martin Schröder. (2012). Sensing Endoplasmic Reticulum Stress. Advances in experimental medicine and biology. 738. 153–168. 88 indexed citations
7.
Cox, David J., et al.. (2011). Measuring Signaling by the Unfolded Protein Response. Methods in enzymology on CD-ROM/Methods in enzymology. 491. 261–292. 19 indexed citations
8.
Parmar, Vipul M., et al.. (2010). Ime1 and Ime2 Are Required for Pseudohyphal Growth of Saccharomyces cerevisiae on Nonfermentable Carbon Sources. Molecular and Cellular Biology. 30(23). 5514–5530. 27 indexed citations
9.
Hodgson, David R. W. & Martin Schröder. (2010). Chemical approaches towards unravelling kinase-mediated signalling pathways. Chemical Society Reviews. 40(3). 1211–1223. 14 indexed citations
10.
Khan, Saeed Uz Zaman & Martin Schröder. (2008). Engineering of chaperone systems and of the unfolded protein response. Cytotechnology. 57(3). 207–231. 34 indexed citations
11.
Schröder, Martin. (2007). Endoplasmic reticulum stress responses. Cellular and Molecular Life Sciences. 65(6). 862–894. 559 indexed citations breakdown →
12.
Schröder, Martin. (2007). Engineering eukaryotic protein factories. Biotechnology Letters. 30(2). 187–196. 49 indexed citations
13.
Back, Sung Hoon, Martin Schröder, Kyung‐Ho Lee, Kezhong Zhang, & Randal J. Kaufman. (2005). ER stress signaling by regulated splicing: IRE1/HAC1/XBP1. Methods. 35(4). 395–416. 184 indexed citations
14.
Schröder, Martin, et al.. (2004). Serum- and protein-free media formulations for the Chinese hamster ovary cell line DUKXB11. Journal of Biotechnology. 108(3). 279–292. 46 indexed citations
15.
Schröder, Martin, Robert L. Clark, Chuan Yin Liu, & Randal J. Kaufman. (2004). The unfolded protein response represses differentiation through the RPD3‐SIN3 histone deacetylase. The EMBO Journal. 23(11). 2281–2292. 32 indexed citations
16.
Schröder, Martin, Robert L. Clark, & Randal J. Kaufman. (2003). IRE1‐ and HAC1‐independent transcriptional regulation in the unfolded protein response of yeast. Molecular Microbiology. 49(3). 591–606. 43 indexed citations
17.
Kaufman, Randal J., Donalyn Scheuner, Martin Schröder, et al.. (2002). The unfolded protein response in nutrient sensing and differentiation. Nature Reviews Molecular Cell Biology. 3(6). 411–421. 502 indexed citations breakdown →
18.
Schröder, Martin, Jason S. Chang, & Randal J. Kaufman. (2000). The unfolded protein response represses nitrogen-starvation induced developmental differentiation in yeast. Genes & Development. 14(23). 2962–2975. 73 indexed citations
19.
Schröder, Martin, Christian Körner, & Peter Friedl. (1999). Quantitative analysis of transcription and translation in gene amplified Chinese hamster ovary cells on the basis of a kinetic model. Cytotechnology. 29(2). 93–102. 11 indexed citations
20.
Schröder, Martin, Klaus Hahlbrock, & Erich Kombrink. (1992). Temporal and spatial patterns of 1, 3‐β‐glucanase and chitinase induction in potato leaves infected by Phytophthora infestans. The Plant Journal. 2(2). 161–172. 88 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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