Deborah S. Wuttke

4.1k total citations
85 papers, 3.2k citations indexed

About

Deborah S. Wuttke is a scholar working on Molecular Biology, Physiology and Materials Chemistry. According to data from OpenAlex, Deborah S. Wuttke has authored 85 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Molecular Biology, 25 papers in Physiology and 11 papers in Materials Chemistry. Recurrent topics in Deborah S. Wuttke's work include DNA Repair Mechanisms (29 papers), Telomeres, Telomerase, and Senescence (25 papers) and RNA and protein synthesis mechanisms (25 papers). Deborah S. Wuttke is often cited by papers focused on DNA Repair Mechanisms (29 papers), Telomeres, Telomerase, and Senescence (25 papers) and RNA and protein synthesis mechanisms (25 papers). Deborah S. Wuttke collaborates with scholars based in United States, Russia and Germany. Deborah S. Wuttke's co-authors include Douglas L. Theobald, Rachel M. Mitton-Fry, Harry B. Gray, Jay R. Winkler, Morten J. Bjerrum, Peter E. Wright, Mark P. Foster, Thayne H. Dickey, Victoria Lundblad and Karen A. Lewis and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Deborah S. Wuttke

84 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deborah S. Wuttke United States 32 2.6k 773 368 308 265 85 3.2k
Beáta G. Vértessy Hungary 35 2.9k 1.1× 147 0.2× 652 1.8× 467 1.5× 207 0.8× 188 3.9k
Grzegorz Piszczek United States 33 2.1k 0.8× 117 0.2× 509 1.4× 245 0.8× 102 0.4× 92 3.3k
Jack J. Skalicky United States 31 2.6k 1.0× 263 0.3× 554 1.5× 156 0.5× 84 0.3× 54 3.4k
Charles R. Kissinger United States 21 4.4k 1.7× 207 0.3× 1.2k 3.2× 548 1.8× 279 1.1× 31 5.5k
Amy E. Keating United States 36 3.7k 1.4× 70 0.1× 516 1.4× 303 1.0× 326 1.2× 94 4.7k
Laurent Lacroix France 35 6.3k 2.4× 186 0.2× 199 0.5× 107 0.3× 164 0.6× 64 6.6k
Daizo Hamada Japan 24 1.9k 0.7× 623 0.8× 644 1.8× 129 0.4× 60 0.2× 52 2.7k
Doug Barrick United States 38 3.6k 1.4× 245 0.3× 1.3k 3.4× 392 1.3× 102 0.4× 89 4.2k
Hidekazu Hiroaki Japan 30 2.5k 0.9× 259 0.3× 444 1.2× 205 0.7× 76 0.3× 98 3.3k
David E. Anderson United States 23 2.5k 1.0× 127 0.2× 729 2.0× 530 1.7× 103 0.4× 43 3.4k

Countries citing papers authored by Deborah S. Wuttke

Since Specialization
Citations

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

Fields of papers citing papers by Deborah S. Wuttke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deborah S. Wuttke. 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 Deborah S. Wuttke. The network helps show where Deborah S. Wuttke may publish in the future.

Co-authorship network of co-authors of Deborah S. Wuttke

This figure shows the co-authorship network connecting the top 25 collaborators of Deborah S. Wuttke. A scholar is included among the top collaborators of Deborah S. Wuttke 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 Deborah S. Wuttke. Deborah S. Wuttke 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.
Batey, Robert, et al.. (2025). A Distinct Mechanism of RNA Recognition by the Transcription Factor GATA1. Biochemistry. 64(6). 1193–1198.
2.
Wuttke, Deborah S., et al.. (2024). The RNA-binding Selectivity of the RGG/RG Motifs of hnRNP U is Abolished by Elements Within the C-terminal Intrinsically Disordered Region. Journal of Molecular Biology. 436(18). 168702–168702. 2 indexed citations
3.
Wuttke, Deborah S., et al.. (2024). Transcription factors ERα and Sox2 have differing multiphasic DNA- and RNA-binding mechanisms. RNA. 30(8). 1089–1105. 1 indexed citations
4.
Wuttke, Deborah S., et al.. (2022). The DNA-Binding High-Mobility Group Box Domain of Sox Family Proteins Directly Interacts with RNA In Vitro. Biochemistry. 61(11). 943–951. 12 indexed citations
5.
Zaug, Arthur J., et al.. (2021). CST does not evict elongating telomerase but prevents initiation by ssDNA binding. Nucleic Acids Research. 49(20). 11653–11665. 22 indexed citations
6.
Lim, Ci Ji, et al.. (2020). The structure of human CST reveals a decameric assembly bound to telomeric DNA. Science. 368(6495). 1081–1085. 68 indexed citations
7.
Batey, Robert, et al.. (2020). hnRNPK recognition of the B motif of Xist and other biological RNAs. Nucleic Acids Research. 48(16). 9320–9335. 32 indexed citations
8.
Rudolph, Johannes, et al.. (2019). Nonspecific Binding of RNA to PARP1 and PARP2 Does Not Lead to Catalytic Activation. Biochemistry. 58(51). 5107–5111. 24 indexed citations
9.
Wuttke, Deborah S., et al.. (2018). Discrimination against RNA Backbones by a ssDNA Binding Protein. Structure. 26(5). 722–733.e2. 1 indexed citations
10.
Guan, Xiaoyang, et al.. (2017). Multimodal Recognition of Diverse Peptides by the C-Terminal SH2 Domain of Phospholipase C-γ1 Protein. Biochemistry. 56(16). 2225–2237. 6 indexed citations
11.
Pinzaru, Alexandra M., Robert A. Hom, Timothy Cardozo, et al.. (2016). Telomere Replication Stress Induced by POT1 Inactivation Accelerates Tumorigenesis. Cell Reports. 15(10). 2170–2184. 89 indexed citations
12.
13.
Alford, John R., C. Andrew Fowler, Deborah S. Wuttke, et al.. (2011). Effect Of Benzyl Alcohol on Recombinant Human Interleukin-1 Receptor Antagonist Structure and Hydrogen–Deuterium Exchange. Journal of Pharmaceutical Sciences. 100(10). 4215–4224. 9 indexed citations
14.
Zappulla, David C., Jennifer N. Roberts, Karen J. Goodrich, Thomas R. Cech, & Deborah S. Wuttke. (2008). Inhibition of yeast telomerase action by the telomeric ssDNA-binding protein, Cdc13p. Nucleic Acids Research. 37(2). 354–367. 26 indexed citations
15.
16.
Theobald, Douglas L. & Deborah S. Wuttke. (2006). Empirical Bayes hierarchical models for regularizing maximum likelihood estimation in the matrix Gaussian Procrustes problem. Proceedings of the National Academy of Sciences. 103(49). 18521–18527. 59 indexed citations
17.
Theobald, Douglas L. & Deborah S. Wuttke. (2005). Accurate structural correlations from maximum likelihood superpositions. PLoS Computational Biology. preprint(2008). e43–e43. 1 indexed citations
18.
Wuttke, Deborah S., et al.. (2003). Electrostatic interactions in the reconstitution of an SH2 domain from constituent peptide fragments. Protein Science. 12(1). 44–55. 6 indexed citations
19.
Mitton-Fry, Rachel M., Emily Anderson, Timothy Hughes, Victoria Lundblad, & Deborah S. Wuttke. (2002). Conserved Structure for Single-Stranded Telomeric DNA Recognition. Science. 296(5565). 145–147. 153 indexed citations
20.
Mitton-Fry, Rachel M. & Deborah S. Wuttke. (2002). 1H, 13C, and 15N resonance assignments of the DNA-binding domain of the essential protein Cdc13 complexed with single-stranded telomeric DNA. Journal of Back and Musculoskeletal Rehabilitation. 22(4). 379–80. 3 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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