Efthymia Papalexi

50.5k total citations · 4 hit papers
12 papers, 16.5k citations indexed

About

Efthymia Papalexi is a scholar working on Molecular Biology, Immunology and Hematology. According to data from OpenAlex, Efthymia Papalexi has authored 12 papers receiving a total of 16.5k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Immunology and 3 papers in Hematology. Recurrent topics in Efthymia Papalexi's work include Single-cell and spatial transcriptomics (9 papers), CRISPR and Genetic Engineering (4 papers) and Hematopoietic Stem Cell Transplantation (3 papers). Efthymia Papalexi is often cited by papers focused on Single-cell and spatial transcriptomics (9 papers), CRISPR and Genetic Engineering (4 papers) and Hematopoietic Stem Cell Transplantation (3 papers). Efthymia Papalexi collaborates with scholars based in United States, Canada and Israel. Efthymia Papalexi's co-authors include Rahul Satija, Peter Smibert, Andrew Butler, Paul Hoffman, Marlon Stoeckius, William M. Mauck, Yuhan Hao, Christoph Hafemeister, Tim Stuart and Eleni P. Mimitou and has published in prestigious journals such as Cell, Nature Genetics and The Journal of Experimental Medicine.

In The Last Decade

Efthymia Papalexi

12 papers receiving 16.4k citations

Hit Papers

Comprehensive Integration... 2017 2026 2020 2023 2019 2018 2017 2019 2.5k 5.0k 7.5k
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. Comprehensive Integration of Single-Cell Data
    2019 7.9k citations Tim Stuart, Andrew Butler et al. Cell profile →
  2. Integrating single-cell transcriptomic data across different conditions, technologies, and species
    2018 6.8k citations Andrew Butler, Paul Hoffman et al. Nature Biotechnology profile →
  3. Single-cell RNA sequencing to explore immune cell heterogeneity
    2017 1.1k citations Efthymia Papalexi, Rahul Satija Nature reviews. Immunology profile →
  4. Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells
    2019 305 citations Eleni P. Mimitou, Anthony Cheng et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Efthymia Papalexi United States 9 10.6k 5.5k 2.5k 2.4k 1.3k 12 16.5k
Andrew Butler United States 10 10.4k 1.0× 5.2k 0.9× 2.5k 1.0× 2.3k 0.9× 1.3k 0.9× 12 16.1k
Peter Smibert United States 28 13.2k 1.2× 6.1k 1.1× 3.5k 1.4× 2.7k 1.1× 1.3k 1.0× 45 19.8k
Christoph Hafemeister United States 12 8.4k 0.8× 3.9k 0.7× 1.8k 0.7× 1.7k 0.7× 821 0.6× 19 12.7k
Allon M. Klein United States 48 10.9k 1.0× 3.6k 0.7× 2.5k 1.0× 3.1k 1.3× 909 0.7× 75 17.2k
Marlon Stoeckius United States 18 7.9k 0.7× 3.5k 0.6× 1.8k 0.7× 1.6k 0.7× 701 0.5× 22 11.7k
Tim Stuart United States 14 7.4k 0.7× 3.2k 0.6× 1.7k 0.7× 1.5k 0.6× 822 0.6× 18 11.4k
Yuhan Hao United States 19 6.3k 0.6× 3.0k 0.6× 1.5k 0.6× 1.5k 0.6× 829 0.6× 38 10.4k
John C. Marioni United Kingdom 73 18.2k 1.7× 3.0k 0.5× 4.6k 1.8× 1.7k 0.7× 761 0.6× 146 23.4k
Orit Rozenblatt–Rosen United States 41 6.7k 0.6× 2.5k 0.5× 1.9k 0.7× 3.1k 1.3× 667 0.5× 61 11.1k
William M. Mauck United States 17 6.1k 0.6× 2.8k 0.5× 1.3k 0.5× 1.3k 0.5× 657 0.5× 24 9.5k

Countries citing papers authored by Efthymia Papalexi

Since Specialization
Citations

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

Fields of papers citing papers by Efthymia Papalexi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Efthymia Papalexi

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

All Works

12 of 12 papers shown
1.
Jiang, Longda, Efthymia Papalexi, Hans‐Hermann Wessels, et al.. (2025). Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens. Nature Cell Biology. 27(3). 505–517. 5 indexed citations
2.
Wessels, Hans‐Hermann, Alejandro Méndez‐Mancilla, Yuhan Hao, et al.. (2022). Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq. Nature Methods. 20(1). 86–94. 47 indexed citations
3.
Papalexi, Efthymia, Eleni P. Mimitou, Andrew Butler, et al.. (2021). Characterizing the molecular regulation of inhibitory immune checkpoints with multimodal single-cell screens. Nature Genetics. 53(3). 322–331. 104 indexed citations
4.
Kaufmann, Kerstin B., Andy G.X. Zeng, Étienne Coyaud, et al.. (2021). A latent subset of human hematopoietic stem cells resists regenerative stress to preserve stemness. Nature Immunology. 22(6). 723–734. 26 indexed citations
5.
Kaufmann, Kerstin B., Andy G.X. Zeng, Étienne Coyaud, et al.. (2020). A Distinct Subset of Human Blood Stem Cells Resists Regenerative Stress to Preserve Stemness. SSRN Electronic Journal. 1 indexed citations
6.
Mimitou, Eleni P., Anthony Cheng, Antonino Montalbano, et al.. (2019). Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nature Methods. 16(5). 409–412. 305 indexed citations breakdown →
7.
Stuart, Tim, Andrew Butler, Paul Hoffman, et al.. (2019). Comprehensive Integration of Single-Cell Data. Cell. 177(7). 1888–1902.e21. 7937 indexed citations breakdown →
8.
Butler, Andrew, Paul Hoffman, Peter Smibert, Efthymia Papalexi, & Rahul Satija. (2018). Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nature Biotechnology. 36(5). 411–420. 6774 indexed citations breakdown →
9.
Upadhaya, Samik, Catherine M. Sawai, Efthymia Papalexi, et al.. (2018). Kinetics of adult hematopoietic stem cell differentiation in vivo. The Journal of Experimental Medicine. 215(11). 2815–2832. 59 indexed citations
10.
Zheng, Shiwei, Efthymia Papalexi, Andrew Butler, William Stephenson, & Rahul Satija. (2018). Molecular transitions in early progenitors during human cord blood hematopoiesis. Molecular Systems Biology. 14(3). e8041–e8041. 100 indexed citations
11.
Papalexi, Efthymia & Rahul Satija. (2017). Single-cell RNA sequencing to explore immune cell heterogeneity. Nature reviews. Immunology. 18(1). 35–45. 1098 indexed citations breakdown →
12.
Viny, Aaron D., Christopher J. Ott, Barbara Spitzer, et al.. (2015). Dose-dependent role of the cohesin complex in normal and malignant hematopoiesis. The Journal of Cell Biology. 211(1). 2111OIA226–2111OIA226. 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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