Hannah Dueck

2.8k total citations · 2 hit papers
13 papers, 1.5k citations indexed

About

Hannah Dueck is a scholar working on Molecular Biology, Cancer Research and Health. According to data from OpenAlex, Hannah Dueck has authored 13 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Cancer Research and 1 paper in Health. Recurrent topics in Hannah Dueck's work include Single-cell and spatial transcriptomics (10 papers), RNA modifications and cancer (2 papers) and Extracellular vesicles in disease (2 papers). Hannah Dueck is often cited by papers focused on Single-cell and spatial transcriptomics (10 papers), RNA modifications and cancer (2 papers) and Extracellular vesicles in disease (2 papers). Hannah Dueck collaborates with scholars based in United States and Türkiye. Hannah Dueck's co-authors include Junhyong Kim, John I. Murray, Sydney M. Shaffer, Eduardo A. Torre, Arjun Raj, Roberto Bonasio, Mingyao Li, Jingshu Wang, Nancy R. Zhang and Mo Huang and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and PLoS ONE.

In The Last Decade

Hannah Dueck

13 papers receiving 1.5k citations

Hit Papers

align trajectories

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.

SAVER: gene expression recovery for single-cell RNA sequencing

2018 458 citations Mo Huang, Jingshu Wang et al. Nature Methods profile →
A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution

2019 301 citations Jonathan S. Packer, Qin Zhu et al. Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hannah Dueck United States	12	1.2k	308	166	139	133	13	1.5k
Yohei Sasagawa Japan	18	1.1k 0.8×	237 0.8×	70 0.4×	111 0.8×	168 1.3×	33	1.4k
Li‐Fang Chu United States	16	1.8k 1.5×	267 0.9×	117 0.7×	109 0.8×	63 0.5×	28	2.0k
Tyler Burks United States	2	1.4k 1.1×	248 0.8×	174 1.0×	213 1.5×	40 0.3×	3	1.7k
Gert‐Jan Hendriks Sweden	14	1.0k 0.8×	461 1.5×	51 0.3×	174 1.3×	213 1.6×	16	1.4k
Karin Aumayr Austria	5	528 0.4×	346 1.1×	91 0.5×	162 1.2×	84 0.6×	6	890
Christopher J. Cronin United States	9	1.3k 1.0×	187 0.6×	293 1.8×	195 1.4×	341 2.6×	13	1.8k
Namit Kumar United States	13	858 0.7×	196 0.6×	110 0.7×	226 1.6×	103 0.8×	17	1.2k
Fabiana M. Duarte United States	12	1.1k 0.9×	213 0.7×	49 0.3×	110 0.8×	83 0.6×	18	1.3k
Nick Burton United Kingdom	20	1.0k 0.8×	124 0.4×	75 0.5×	126 0.9×	285 2.1×	40	1.6k

Countries citing papers authored by Hannah Dueck

Since Specialization

Citations

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

Fields of papers citing papers by Hannah Dueck

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hannah Dueck

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Shams‐White, Marissa, Rolando Barajas, Roxanne E. Jensen, et al.. (2021). Systems epidemiology and cancer: A review of the National Institutes of Health extramural grant portfolio 2013–2018. PLoS ONE. 16(4). e0250061–e0250061. 4 indexed citations

2.

Packer, Jonathan S., Qin Zhu, Chau Huynh, et al.. (2019). A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution. Science. 365(6459). 301 indexed citations breakdown →

3.

Wang, Jingshu, Mo Huang, Eduardo A. Torre, et al.. (2018). Gene expression distribution deconvolution in single-cell RNA sequencing. Proceedings of the National Academy of Sciences. 115(28). E6437–E6446. 63 indexed citations

4.

Zhu, Qin, Stephen Fisher, Hannah Dueck, et al.. (2018). PIVOT: platform for interactive analysis and visualization of transcriptomics data. BMC Bioinformatics. 19(1). 6–6. 29 indexed citations

5.

Huang, Mo, Jingshu Wang, Eduardo A. Torre, et al.. (2018). SAVER: gene expression recovery for single-cell RNA sequencing. Nature Methods. 15(7). 539–542. 458 indexed citations breakdown →

6.

Torre, Eduardo A., Hannah Dueck, Sydney M. Shaffer, et al.. (2018). Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH. Cell Systems. 6(2). 171–179.e5. 77 indexed citations

7.

Dueck, Hannah, James Eberwine, & Junhyong Kim. (2015). Variation is function: Are single cell differences functionally important?. BioEssays. 38(2). 172–180. 58 indexed citations

8.

Dueck, Hannah, Mugdha Khaladkar, Tae Kyung Kim, et al.. (2015). Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation. Genome Biology. 16(1). 122–122. 66 indexed citations

9.

Spaethling, Jennifer, Manuel Sánchez-Alavez, Jaehee Lee, et al.. (2015). Single‐cell transcriptomics and functional target validation of brown adipocytes show their complex roles in metabolic homeostasis. The FASEB Journal. 30(1). 81–92. 36 indexed citations

10.

Lahens, Nicholas F., İbrahim Halil Kavaklı, Ray Zhang, et al.. (2014). IVT-seq reveals extreme bias in RNA sequencing. Genome biology. 15(6). R86–R86. 110 indexed citations

11.

Lovatt, Ditte, Brittani K. Ruble, Jaehee Lee, et al.. (2014). Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue. Nature Methods. 11(2). 190–196. 211 indexed citations

12.

Spaethling, Jennifer, David Piel, Hannah Dueck, et al.. (2013). Serotonergic neuron regulation informed by in vivo single‐cell transcriptomics. The FASEB Journal. 28(2). 771–780. 46 indexed citations

13.

Eberwine, James, Ditte Lovatt, Peter T. Buckley, et al.. (2012). Quantitative biology of single neurons. Journal of The Royal Society Interface. 9(77). 3165–3183. 16 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.

Explore authors with similar magnitude of impact