Natalie Stanley

2.7k total citations
34 papers, 371 citations indexed

About

Natalie Stanley is a scholar working on Molecular Biology, Artificial Intelligence and Biophysics. According to data from OpenAlex, Natalie Stanley has authored 34 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 6 papers in Artificial Intelligence and 5 papers in Biophysics. Recurrent topics in Natalie Stanley's work include Single-cell and spatial transcriptomics (10 papers), Gene Regulatory Network Analysis (5 papers) and Cell Image Analysis Techniques (5 papers). Natalie Stanley is often cited by papers focused on Single-cell and spatial transcriptomics (10 papers), Gene Regulatory Network Analysis (5 papers) and Cell Image Analysis Techniques (5 papers). Natalie Stanley collaborates with scholars based in United States, Austria and Australia. Natalie Stanley's co-authors include Peter J. Mucha, Thomas Bonacci, Roland Kwitt, Marc Niethammer, Saray Shai, Dane Taylor, Gavin D. Grant, Jeanette Gowen Cook, Nicholas G. Brown and Michael J. Emanuele and has published in prestigious journals such as Physical Review Letters, Nature Communications and The EMBO Journal.

In The Last Decade

Natalie Stanley

30 papers receiving 362 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Natalie Stanley United States 9 185 79 66 49 38 34 371
Aleksandar Stojmirović United States 11 361 2.0× 78 1.0× 63 1.0× 75 1.5× 65 1.7× 25 675
Ioannis Iliopoulos Greece 14 399 2.2× 34 0.4× 83 1.3× 86 1.8× 39 1.0× 27 627
Evangelos Karatzas Greece 12 298 1.6× 35 0.4× 30 0.5× 21 0.4× 21 0.6× 29 475
Zahra Razaghi‐Moghadam Germany 11 374 2.0× 97 1.2× 50 0.8× 17 0.3× 13 0.3× 33 597
Alberto Valdeolivas Germany 7 476 2.6× 30 0.4× 39 0.6× 96 2.0× 69 1.8× 13 679
Silpa Suthram United States 7 984 5.3× 39 0.5× 36 0.5× 37 0.8× 26 0.7× 11 1.1k
Somaye Hashemifar United States 9 488 2.6× 39 0.5× 52 0.8× 55 1.1× 16 0.4× 14 627
Jason Yao Taiwan 9 268 1.4× 26 0.3× 13 0.2× 60 1.2× 31 0.8× 21 449
Sabine Hug Germany 8 297 1.6× 25 0.3× 50 0.8× 17 0.3× 25 0.7× 10 448

Countries citing papers authored by Natalie Stanley

Since Specialization
Citations

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

Fields of papers citing papers by Natalie Stanley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalie Stanley

This figure shows the co-authorship network connecting the top 25 collaborators of Natalie Stanley. A scholar is included among the top collaborators of Natalie Stanley 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 Natalie Stanley. Natalie Stanley 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.
Kollipara, Avinash, Chengwen Li, Xiaojing Zheng, et al.. (2025). T cell signatures associated with reduced Chlamydia trachomatis reinfection in a highly exposed cohort. JCI Insight. 10(7). 1 indexed citations
2.
Green, William D., Nancy P. Kren, Jennifer L. Modliszewski, et al.. (2025). Enhancer-driven gene regulatory networks reveal transcription factors governing T cell adaptation and differentiation in the tumor microenvironment. Immunity. 58(7). 1725–1741.e9. 6 indexed citations
3.
Stanley, Natalie, et al.. (2025). Microglia Single‐Cell RNA‐Seq Enables Robust and Applicable Markers of Biological Aging. Aging Cell. 24(8). e70095–e70095.
4.
Stanley, Natalie, et al.. (2024). Cellograph: a semi-supervised approach to analyzing multi-condition single-cell RNA-sequencing data using graph neural networks. BMC Bioinformatics. 25(1). 25–25. 5 indexed citations
5.
Ranek, Jolene S., Wayne Stallaert, J. Justin Milner, et al.. (2024). DELVE: feature selection for preserving biological trajectories in single-cell data. Nature Communications. 15(1). 2765–2765. 7 indexed citations
6.
7.
Li, Xiaoyan, et al.. (2024). Use High-dimensional Immune Profiling to Study Peripheral Immune System and ALS Progression (P6-11.006). Neurology. 102(17_supplement_1). 1 indexed citations
8.
Kollipara, Avinash, Chengwen Li, Xiaojing Zheng, et al.. (2024). Unique T cell signatures are associated with reduced Chlamydia trachomatis reinfection in a highly exposed cohort.. The Journal of Immunology. 212(1_Supplement). 0986_5627–0986_5627. 1 indexed citations
9.
Weideman, Ann Marie, Jolene S. Ranek, JoAnn Kuruc, et al.. (2023). Dominant CD4+ T cell receptors remain stable throughout antiretroviral therapy-mediated immune restoration in people with HIV. Cell Reports Medicine. 4(11). 101268–101268. 4 indexed citations
10.
Ranek, Jolene S., Natalie Stanley, & Jeremy E. Purvis. (2022). Integrating temporal single-cell gene expression modalities for trajectory inference and disease prediction. Genome biology. 23(1). 186–186. 7 indexed citations
11.
12.
Liechti, Thomas, Lukas M. Weber, Thomas M. Ashhurst, et al.. (2021). An updated guide for the perplexed: cytometry in the high-dimensional era. Nature Immunology. 22(10). 1190–1197. 48 indexed citations
13.
Ganio, Edward A., Natalie Stanley, Jakob Einhaus, et al.. (2020). Preferential inhibition of adaptive immune system dynamics by glucocorticoids in patients after acute surgical trauma. Nature Communications. 11(1). 3737–3737. 17 indexed citations
14.
Stanley, Natalie, et al.. (2020). Three Months of Treatment With Esketamine. The Primary Care Companion For CNS Disorders. 22(4). 4 indexed citations
15.
Phongpreecha, Thanaphong, Rosemary Fernandez, Dunja Mrdjen, et al.. (2020). Single-cell peripheral immunoprofiling of Alzheimer’s and Parkinson’s diseases. Science Advances. 6(48). 30 indexed citations
16.
Stanley, Natalie, Thomas Bonacci, Roland Kwitt, Marc Niethammer, & Peter J. Mucha. (2019). Stochastic block models with multiple continuous attributes. Applied Network Science. 4(1). 36 indexed citations
17.
Bonacci, Thomas, Aussie Suzuki, Gavin D. Grant, et al.. (2018). Cezanne/ OTUD 7B is a cell cycle‐regulated deubiquitinase that antagonizes the degradation of APC /C substrates. The EMBO Journal. 37(16). 71 indexed citations
18.
Stanley, Natalie, Roland Kwitt, Marc Niethammer, & Peter J. Mucha. (2018). Compressing Networks with Super Nodes. Scientific Reports. 8(1). 10892–10892. 22 indexed citations
19.
Taylor, Dane, Saray Shai, Natalie Stanley, & Peter J. Mucha. (2016). Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation. Physical Review Letters. 116(22). 228301–228301. 48 indexed citations
20.
Parry, Traci L., Jonathan C. Schisler, Luge Li, et al.. (2015). Fenofibrate unexpectedly induces cardiac hypertrophy in mice lacking MuRF1. Cardiovascular Pathology. 25(2). 127–140. 9 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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