Sandy Klemm

4.7k total citations · 2 hit papers
15 papers, 2.7k citations indexed

About

Sandy Klemm is a scholar working on Molecular Biology, Biomedical Engineering and Immunology. According to data from OpenAlex, Sandy Klemm has authored 15 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 3 papers in Biomedical Engineering and 2 papers in Immunology. Recurrent topics in Sandy Klemm's work include Single-cell and spatial transcriptomics (5 papers), Innovative Microfluidic and Catalytic Techniques Innovation (2 papers) and Pluripotent Stem Cells Research (2 papers). Sandy Klemm is often cited by papers focused on Single-cell and spatial transcriptomics (5 papers), Innovative Microfluidic and Catalytic Techniques Innovation (2 papers) and Pluripotent Stem Cells Research (2 papers). Sandy Klemm collaborates with scholars based in United States, Sweden and Netherlands. Sandy Klemm's co-authors include William J. Greenleaf, Zohar Shipony, Alexander van Oudenaarden, Rudolf Jaenisch, Dina A. Faddah, Albert W. Cheng, Kibibi Ganz, Styliani Markoulaki, Yosef Buganim and Nils Blüthgen and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Sandy Klemm

15 papers receiving 2.7k 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.

Chromatin accessibility and the regulatory epigenome

2019 1.0k citations Sandy Klemm, Zohar Shipony et al. Nature Reviews Genetics profile →
Single-Cell Expression Analyses during Cellular Reprogramming Reveal an Early Stochastic and a Late Hierarchic Phase

2012 626 citations Yosef Buganim, Dina A. Faddah et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sandy Klemm United States	12	2.2k	459	292	236	229	15	2.7k
Itoshi Nikaido Japan	23	1.8k 0.8×	373 0.8×	172 0.6×	323 1.4×	129 0.6×	46	2.3k
Alon Goren United States	21	3.3k 1.5×	638 1.4×	436 1.5×	506 2.1×	193 0.8×	35	4.0k
Reza Kalhor United States	17	2.2k 1.0×	351 0.8×	182 0.6×	283 1.2×	246 1.1×	19	2.6k
Michael L. Gonzales United States	13	2.0k 0.9×	376 0.8×	247 0.8×	476 2.0×	140 0.6×	21	2.4k
Sergi Regot United States	18	1.9k 0.9×	287 0.6×	151 0.5×	140 0.6×	112 0.5×	27	2.3k
Robert P. Zinzen Germany	19	2.1k 0.9×	305 0.7×	144 0.5×	310 1.3×	334 1.5×	26	2.3k
Yodai Takei United States	8	2.4k 1.1×	332 0.7×	259 0.9×	263 1.1×	238 1.0×	11	2.7k
Li‐Fang Chu United States	16	1.8k 0.8×	267 0.6×	109 0.4×	187 0.8×	111 0.5×	28	2.0k
Fuchou Tang United Kingdom	6	2.6k 1.1×	1.1k 2.3×	442 1.5×	276 1.2×	135 0.6×	7	3.1k
Angela Ruohao Wu Hong Kong	24	2.2k 1.0×	492 1.1×	327 1.1×	181 0.8×	83 0.4×	58	3.1k

Countries citing papers authored by Sandy Klemm

Since Specialization

Citations

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

Fields of papers citing papers by Sandy Klemm

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sandy Klemm

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

All Works

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15 of 15 papers shown

1.

Klemm, Sandy, et al.. (2025). Thymic epithelial cells amplify epigenetic noise to promote immune tolerance. Nature. 646(8085). 724–733. 1 indexed citations

2.

Parks, Benjamin, et al.. (2024). PU.1 and BCL11B sequentially cooperate with RUNX1 to anchor mSWI/SNF to poise the T cell effector landscape. Nature Immunology. 25(5). 860–872. 12 indexed citations

3.

Khariton, Margarita, Conor J. McClune, Sandy Klemm, et al.. (2023). Alleviating Cell Lysate-Induced Inhibition to Enable RT-PCR from Single Cells in Picoliter-Volume Double Emulsion Droplets. Analytical Chemistry. 95(2). 935–945. 3 indexed citations

4.

Blum, Jacob A., Sandy Klemm, Jennifer L. Shadrach, et al.. (2021). Single-cell transcriptomic analysis of the adult mouse spinal cord reveals molecular diversity of autonomic and skeletal motor neurons. Nature Neuroscience. 24(4). 572–583. 107 indexed citations

5.

Carswell-Crumpton, Catherine, Sandy Klemm, Bianca Cruz, et al.. (2020). Double emulsion flow cytometry with high-throughput single droplet isolation and nucleic acid recovery. Lab on a Chip. 20(12). 2062–2074. 78 indexed citations

6.

Granja, Jeffrey M., Sandy Klemm, Lisa McGinnis, et al.. (2019). Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia. Nature Biotechnology. 37(12). 1458–1465. 257 indexed citations

7.

Klemm, Sandy, Zohar Shipony, & William J. Greenleaf. (2019). Chromatin accessibility and the regulatory epigenome. Nature Reviews Genetics. 20(4). 207–220. 1001 indexed citations breakdown →

8.

Mezger, Anja, Sandy Klemm, Ishminder K. Mann, et al.. (2018). High-throughput chromatin accessibility profiling at single-cell resolution. Nature Communications. 9(1). 3647–3647. 105 indexed citations

9.

Schmiedel, Jörn M., Sandy Klemm, Yannan Zheng, et al.. (2015). MicroRNA control of protein expression noise. Science. 348(6230). 128–132. 281 indexed citations

10.

Klemm, Sandy, Stefan Semrau, Kay Wiebrands, et al.. (2014). Transcriptional profiling of cells sorted by RNA abundance. Nature Methods. 11(5). 549–551. 26 indexed citations

11.

Buganim, Yosef, Dina A. Faddah, Albert W. Cheng, et al.. (2012). Single-Cell Expression Analyses during Cellular Reprogramming Reveal an Early Stochastic and a Late Hierarchic Phase. Cell. 150(6). 1209–1222. 626 indexed citations breakdown →

12.

Bienko, Magda, Nicola Crosetto, Lenny Teytelman, et al.. (2012). A versatile genome-scale PCR-based pipeline for high-definition DNA FISH. Nature Methods. 10(2). 122–124. 48 indexed citations

13.

Ramsey, Stephen A., Sandy Klemm, Daniel E. Zak, et al.. (2008). Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics. PLoS Computational Biology. 4(3). e1000021–e1000021. 144 indexed citations

14.

Ramsey, Stephen A., Sandy Klemm, Daniel E. Zak, et al.. (2008). Correction: Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics. PLoS Computational Biology. 4(4). 5 indexed citations

15.

Ramsey, Stephen A., Sandy Klemm, Daniel E. Zak, et al.. (2008). Correction: Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics. PLoS Computational Biology. 4(3). 11 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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