Debora S. Marks

33.7k total citations · 14 hit papers
102 papers, 21.4k citations indexed

About

Debora S. Marks is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Debora S. Marks has authored 102 papers receiving a total of 21.4k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Molecular Biology, 25 papers in Genetics and 22 papers in Cancer Research. Recurrent topics in Debora S. Marks's work include Protein Structure and Dynamics (30 papers), RNA and protein synthesis mechanisms (25 papers) and MicroRNA in disease regulation (18 papers). Debora S. Marks is often cited by papers focused on Protein Structure and Dynamics (30 papers), RNA and protein synthesis mechanisms (25 papers) and MicroRNA in disease regulation (18 papers). Debora S. Marks collaborates with scholars based in United States, United Kingdom and Germany. Debora S. Marks's co-authors include Chris Sander, Thomas Tuschl, Bino John, Anton J. Enright, Alexei A. Aravin, Thomas A. Hopf, Doron Betel, Ulrike Gaul, Michael T. Wilson and Aaron Gabow and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Debora S. Marks

101 papers receiving 21.2k citations

Hit Papers

Human MicroRNA Targets 2003 2026 2010 2018 2004 2003 2007 2004 2011 1000 2.0k 3.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Human MicroRNA Targets
    2004 3.1k citations Chris Sander, Debora S. Marks et al. profile →
  2. MicroRNA targets in Drosophila
    2003 2.8k citations Chris Sander, Debora S. Marks et al. profile →
  3. The microRNA.org resource: targets and expression
    2007 2.1k citations Debora S. Marks, Chris Sander et al. profile →
  4. Identification of Virus-Encoded MicroRNAs
    2004 1.2k citations Debora S. Marks, Chris Sander et al. Science profile →
  5. Direct-coupling analysis of residue coevolution captures native contacts across many protein families
    2011 971 citations Debora S. Marks, Chris Sander et al. Proceedings of the National Academy of Sciences profile →
  6. Protein 3D Structure Computed from Evolutionary Sequence Variation
    2011 762 citations Debora S. Marks, Robert P. Sheridan et al. profile →
  7. The Small RNA Profile during Drosophila melanogaster Development
    2003 751 citations Debora S. Marks et al. profile →
  8. miR-122, a Mammalian Liver-Specific microRNA, is Processed from hcr mRNA and MayDownregulate the High Affinity Cationic Amino Acid Transporter CAT-1
    2004 696 citations Debora S. Marks, Chris Sander et al. profile →
  9. miRcode: a map of putative microRNA target sites in the long non-coding transcriptome
    2012 580 citations Debora S. Marks et al. Bioinformatics profile →
  10. Mutation effects predicted from sequence co-variation
    2017 447 citations Thomas A. Hopf, John Ingraham et al. Nature Biotechnology profile →
  11. Disease variant prediction with deep generative models of evolutionary data
    2021 375 citations Pascal Notin, Joseph Min et al. Nature profile →
  12. Protein design and variant prediction using autoregressive generative models
    2021 195 citations Jung-Eun Shin, Adam J. Riesselman et al. Nature Communications profile →
  13. Machine learning for functional protein design
    2024 118 citations Pascal Notin, Nathan Rollins et al. Nature Biotechnology profile →
  14. Learning from prepandemic data to forecast viral escape
    2023 85 citations Pascal Notin, Daniel P. Ritter et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Debora S. Marks United States 53 17.1k 10.0k 2.2k 1.4k 1.3k 102 21.4k
Robert M. Stephens United States 64 13.3k 0.8× 5.9k 0.6× 2.1k 0.9× 1.8k 1.3× 1.0k 0.8× 151 19.1k
Anton J. Enright United Kingdom 60 21.9k 1.3× 14.6k 1.5× 1.7k 0.8× 2.4k 1.8× 2.7k 2.1× 122 27.9k
David J. Galas United States 58 13.9k 0.8× 5.7k 0.6× 4.1k 1.8× 2.5k 1.8× 921 0.7× 144 20.7k
Alexey I. Nesvizhskii United States 66 20.0k 1.2× 2.4k 0.2× 1.4k 0.6× 1.6k 1.2× 989 0.8× 228 26.6k
Paul D. Thomas United States 39 13.7k 0.8× 2.1k 0.2× 3.4k 1.5× 1.7k 1.3× 1.9k 1.5× 74 21.0k
Akhilesh Pandey United States 89 20.8k 1.2× 3.6k 0.4× 1.6k 0.7× 2.8k 2.1× 812 0.6× 502 31.6k
Juri Rappsilber United Kingdom 76 23.7k 1.4× 2.1k 0.2× 2.7k 1.2× 1.4k 1.0× 2.3k 1.8× 291 29.0k
Roy Parker United States 103 39.0k 2.3× 5.3k 0.5× 1.6k 0.7× 1.6k 1.2× 2.5k 2.0× 259 43.7k
Miguel A. Andrade‐Navarro Germany 60 11.9k 0.7× 1.9k 0.2× 1.3k 0.6× 822 0.6× 849 0.7× 268 15.3k
Nicholas D. Socci United States 74 13.5k 0.8× 3.2k 0.3× 1.8k 0.8× 1.5k 1.1× 539 0.4× 158 21.6k

Countries citing papers authored by Debora S. Marks

Since Specialization
Citations

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

Fields of papers citing papers by Debora S. Marks

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debora S. Marks

This figure shows the co-authorship network connecting the top 25 collaborators of Debora S. Marks. A scholar is included among the top collaborators of Debora S. Marks 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 Debora S. Marks. Debora S. Marks 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.
Gado, Japheth E., et al.. (2025). Machine learning prediction of enzyme optimum pH. Nature Machine Intelligence. 7(5). 716–729. 10 indexed citations
2.
Zheng, Chunlei, Daniel P. Ritter, Debora S. Marks, et al.. (2025). Pancreatic cancer risk prediction using deep sequential modeling of longitudinal diagnostic and medication records. Cell Reports Medicine. 6(9). 102359–102359.
3.
Notin, Pascal, Nathan Rollins, Yarin Gal, Chris Sander, & Debora S. Marks. (2024). Machine learning for functional protein design. Nature Biotechnology. 42(2). 216–228. 118 indexed citations breakdown →
4.
Rix, Gordon, et al.. (2024). Continuous evolution of user-defined genes at 1 million times the genomic mutation rate. Science. 386(6722). eadm9073–eadm9073. 16 indexed citations
5.
Hummels, Katherine R., Zhaoqi Li, Atsushi Taguchi, et al.. (2023). Coordination of bacterial cell wall and outer membrane biosynthesis. Nature. 615(7951). 300–304. 47 indexed citations
6.
Höcker, Birte, Peilong Lu, Anum Glasgow, et al.. (2023). How can the protein design community best support biologists who want to harness AI tools for protein structure prediction and design?. Cell Systems. 14(8). 629–632. 1 indexed citations
7.
Erlandson, Sarah C., Shaun Rawson, James Osei‐Owusu, et al.. (2023). The relaxin receptor RXFP1 signals through a mechanism of autoinhibition. Nature Chemical Biology. 19(8). 1013–1021. 11 indexed citations
8.
Ding, David, Anna G. Green, Boyuan Wang, et al.. (2022). Co-evolution of interacting proteins through non-contacting and non-specific mutations. Nature Ecology & Evolution. 6(5). 590–603. 23 indexed citations
9.
Akyuz, Nurunisa, K. Domenica Karavitaki, Bifeng Pan, et al.. (2022). Mechanical gating of the auditory transduction channel TMC1 involves the fourth and sixth transmembrane helices. Science Advances. 8(28). eabo1126–eabo1126. 16 indexed citations
10.
Shin, Jung-Eun, Meredith A. Skiba, Alon Wellner, et al.. (2022). An in silico method to assess antibody fragment polyreactivity. Nature Communications. 13(1). 7554–7554. 28 indexed citations
11.
Wellner, Alon, Conor McMahon, Morgan S. A. Gilman, et al.. (2021). Rapid generation of potent antibodies by autonomous hypermutation in yeast. Nature Chemical Biology. 17(10). 1057–1064. 77 indexed citations
12.
Sjodt, Megan, Patricia D. A. Rohs, Morgan S. A. Gilman, et al.. (2020). Structural coordination of polymerization and crosslinking by a SEDS–bPBP peptidoglycan synthase complex. Nature Microbiology. 5(6). 813–820. 93 indexed citations
13.
Stiffler, Michael A., Frank J. Poelwijk, Kelly P. Brock, et al.. (2019). Protein Structure from Experimental Evolution. Cell Systems. 10(1). 15–24.e5. 25 indexed citations
14.
Nicoludis, John M., Anna G. Green, Sanket Walujkar, et al.. (2019). Interaction specificity of clustered protocadherins inferred from sequence covariation and structural analysis. Proceedings of the National Academy of Sciences. 116(36). 17825–17830. 25 indexed citations
15.
Schubert, Benjamin, Rohan Maddamsetti, Jackson Nyman, Maha Farhat, & Debora S. Marks. (2018). Genome-wide discovery of epistatic loci affecting antibiotic resistance in Neisseria gonorrhoeae using evolutionary couplings. Nature Microbiology. 4(2). 328–338. 31 indexed citations
16.
Zheng, Sanduo, Lok‐To Sham, Kelly P. Brock, et al.. (2018). Structure and mutagenic analysis of the lipid II flippase MurJ from Escherichia coli. Proceedings of the National Academy of Sciences. 115(26). 6709–6714. 50 indexed citations
17.
Hopf, Thomas A., Anna G. Green, Benjamin Schubert, et al.. (2018). The EVcouplings Python framework for coevolutionary sequence analysis. Bioinformatics. 35(9). 1582–1584. 172 indexed citations
18.
Maddamsetti, Rohan, et al.. (2018). Gain‐of‐function experiments with bacteriophage lambda uncover residues under diversifying selection in nature. Evolution. 72(10). 2234–2243. 12 indexed citations
19.
Schmiedel, Jörn M., Sandy Klemm, Yannan Zheng, et al.. (2015). MicroRNA control of protein expression noise. Science. 348(6230). 128–132. 281 indexed citations
20.
Hayat, Sikander, Chris Sander, Debora S. Marks, & Arne Elofsson. (2015). All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences. Proceedings of the National Academy of Sciences. 112(17). 5413–5418. 42 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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