Dana L. Jackson

5.7k total citations · 2 hit papers
27 papers, 1.8k citations indexed

About

Dana L. Jackson is a scholar working on Molecular Biology, Epidemiology and Cell Biology. According to data from OpenAlex, Dana L. Jackson has authored 27 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 5 papers in Epidemiology and 5 papers in Cell Biology. Recurrent topics in Dana L. Jackson's work include Single-cell and spatial transcriptomics (16 papers), Zebrafish Biomedical Research Applications (5 papers) and RNA Research and Splicing (5 papers). Dana L. Jackson is often cited by papers focused on Single-cell and spatial transcriptomics (16 papers), Zebrafish Biomedical Research Applications (5 papers) and RNA Research and Splicing (5 papers). Dana L. Jackson collaborates with scholars based in United States, South Africa and Bangladesh. Dana L. Jackson's co-authors include Cole Trapnell, Jay Shendure, José L. McFaline‐Figueroa, Andrew J. Hill, Jonathan S. Packer, Sanjay Srivatsan, Xiaojie Qiu, Molly Gasperini, Frank J. Steemers and Hannah A. Pliner and has published in prestigious journals such as Science, Cell and Nature Communications.

In The Last Decade

Dana L. Jackson

26 papers receiving 1.8k citations

Hit Papers

Cicero Predicts cis-Regulatory DNA Interactions from Sing... 2018 2026 2020 2023 2018 2019 100 200 300 400

Peers

Dana L. Jackson
Sanjay Srivatsan United States
Scott N. Furlan United States
Jeffrey A. Hussmann United States
Claire E. Hirst Australia
Dave Gennert United States
Klaas W. Mulder Netherlands
Kieran M. Short Australia
Sanjay Srivatsan United States
Dana L. Jackson
Citations per year, relative to Dana L. Jackson Dana L. Jackson (= 1×) peers Sanjay Srivatsan

Countries citing papers authored by Dana L. Jackson

Since Specialization
Citations

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

Fields of papers citing papers by Dana L. Jackson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dana L. Jackson. 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 Dana L. Jackson. The network helps show where Dana L. Jackson may publish in the future.

Co-authorship network of co-authors of Dana L. Jackson

This figure shows the co-authorship network connecting the top 25 collaborators of Dana L. Jackson. A scholar is included among the top collaborators of Dana L. Jackson 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 Dana L. Jackson. Dana L. Jackson 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.
Ishida, Takashi, Adam Heck, Ian G. Phelps, et al.. (2025). Differentiation latency and dormancy signatures define fetal liver hematopoietic stem cells at single-cell resolution. Cell Reports. 44(10). 116289–116289.
2.
McFaline‐Figueroa, José L., Sanjay Srivatsan, Andrew J. Hill, et al.. (2024). Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy. Cell Genomics. 4(2). 100487–100487. 10 indexed citations
3.
Massouridès, Emmanuelle, Virginie Mournetas, Dana L. Jackson, et al.. (2024). Dystrophin deficiency impairs cell junction formation during embryonic myogenesis from pluripotent stem cells. iScience. 27(7). 110242–110242. 1 indexed citations
4.
Read, David F., Gregory T. Booth, Riza M. Daza, et al.. (2024). Single-cell analysis of chromatin and expression reveals age- and sex-associated alterations in the human heart. Communications Biology. 7(1). 1052–1052. 5 indexed citations
5.
Dorrity, Michael W., Lauren M. Saunders, Madeleine Duran, et al.. (2023). Proteostasis governs differential temperature sensitivity across embryonic cell types. Cell. 186(23). 5015–5027.e12. 20 indexed citations
6.
Hadland, Brandon, Barbara Varnum‐Finney, Adam Heck, et al.. (2022). Engineering a niche supporting hematopoietic stem cell development using integrated single-cell transcriptomics. Nature Communications. 13(1). 1584–1584. 28 indexed citations
7.
Bonora, Giancarlo, Vijay Ramani, Ritambhara Singh, et al.. (2021). Single-cell landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation. Genome biology. 22(1). 279–279. 16 indexed citations
8.
Varnum‐Finney, Barbara, Sanjay Srivatsan, Adam Heck, et al.. (2021). Multipotent progenitors and hematopoietic stem cells arise independently from hemogenic endothelium in the mouse embryo. Cell Reports. 36(11). 109675–109675. 60 indexed citations
9.
Sridhar, Akshayalakshmi, Akina Hoshino, Connor Finkbeiner, et al.. (2020). Single-Cell Transcriptomic Comparison of Human Fetal Retina, hPSC-Derived Retinal Organoids, and Long-Term Retinal Cultures. Cell Reports. 30(5). 1644–1659.e4. 179 indexed citations
10.
Gustafson, Heather H., et al.. (2020). Trajectory analysis quantifies transcriptional plasticity during macrophage polarization. Scientific Reports. 10(1). 12273–12273. 67 indexed citations
11.
Srivatsan, Sanjay, Heather Z Huang, Jason J. Stephany, et al.. (2020). High‐throughput, microscope‐based sorting to dissect cellular heterogeneity. Molecular Systems Biology. 16(6). e9442–e9442. 46 indexed citations
12.
Srivatsan, Sanjay, José L. McFaline‐Figueroa, Vijay Ramani, et al.. (2019). Massively multiplex chemical transcriptomics at single-cell resolution. Science. 367(6473). 45–51. 198 indexed citations
13.
Gasperini, Molly, Andrew J. Hill, José L. McFaline‐Figueroa, et al.. (2019). A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens. Cell. 176(1-2). 377–390.e19. 370 indexed citations breakdown →
14.
McFaline‐Figueroa, José L., Andrew J. Hill, Xiaojie Qiu, et al.. (2019). A pooled single-cell genetic screen identifies regulatory checkpoints in the continuum of the epithelial-to-mesenchymal transition. Nature Genetics. 51(9). 1389–1398. 119 indexed citations
15.
Pliner, Hannah A., Jonathan S. Packer, José L. McFaline‐Figueroa, et al.. (2018). Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data. Molecular Cell. 71(5). 858–871.e8. 413 indexed citations breakdown →
16.
Hill, Andrew J., José L. McFaline‐Figueroa, Lea M. Starita, et al.. (2018). On the design of CRISPR-based single-cell molecular screens. Nature Methods. 15(4). 271–274. 134 indexed citations
17.
Craig, Karen, Dana L. Jackson, Gregory Engel, et al.. (2015). A Seminomadic Population in Bangladesh with Extensive Exposure to Macaques Does Not Exhibit High Levels of Zoonotic Simian Foamy Virus Infection. Journal of Virology. 89(14). 7414–7416. 6 indexed citations
18.
Engel, Gregory, M. Andreína Pacheco, JoAnn L. Yee, et al.. (2013). Population dynamics of rhesus macaques and associated foamy virus in Bangladesh. Emerging Microbes & Infections. 2(1). 1–14. 31 indexed citations
19.
Jackson, Dana L., et al.. (2011). The DEAD-box RNA Helicase DDX6 is Required for Efficient Encapsidation of a Retroviral Genome. PLoS Pathogens. 7(10). e1002303–e1002303. 47 indexed citations
20.
Jackson, Dana L., et al.. (2010). Foamy Retrovirus Integrase Contains a Pol Dimerization Domain Required for Protease Activation. Journal of Virology. 85(4). 1655–1661. 13 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

Rankless by CCL
2026