Andrew Earl

2.3k total citations · 1 hit paper
10 papers, 1.0k citations indexed

About

Andrew Earl is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Andrew Earl has authored 10 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 1 paper in Pulmonary and Respiratory Medicine and 1 paper in Oncology. Recurrent topics in Andrew Earl's work include Single-cell and spatial transcriptomics (4 papers), RNA Research and Splicing (4 papers) and Genomics and Chromatin Dynamics (4 papers). Andrew Earl is often cited by papers focused on Single-cell and spatial transcriptomics (4 papers), RNA Research and Splicing (4 papers) and Genomics and Chromatin Dynamics (4 papers). Andrew Earl collaborates with scholars based in United States. Andrew Earl's co-authors include Jason D. Buenrostro, Zachary Chiang, Caleb A. Lareau, Lindsay M. LaFave, Vinay K. Kartha, Yan Hu, Sai Ma, Tristan Tay, Jiarui Ding and Bing Zhang and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Andrew Earl

10 papers receiving 1.0k 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 Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin

2020 579 citations Sai Ma, Bing Zhang et al. Cell profile →

Peers

Andrew Earl

MB

CR

BIOPH

IMMUN

GENET

Bastiaan Spanjaard Germany

Bianka Baying Germany

Xiuwei Zhang United Kingdom

Alison Brack United States

Tamir Biezuner Israel

Swati Parekh Germany

Zachary Chiang United States

Carolina Guibentif Sweden

Vitalii Kleshchevnikov United Kingdom

Mubeen Goolam South Africa

Bastiaan Spanjaard Germany

Andrew Earl

895 ×1.0

MB

255 ×1.2

CR

113 ×0.8

BIOPH

93 ×0.8

IMMUN

97 ×1.2

GENET

Citations per year, relative to Andrew Earl Andrew Earl (= 1×) peers Bastiaan Spanjaard

Countries citing papers authored by Andrew Earl

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Earl

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Earl

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

All Works

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10 of 10 papers shown

1.

Labade, Ajay S., Zachary Chiang, Paul Reginato, et al.. (2025). Expansion in situ genome sequencing links nuclear abnormalities to aberrant chromatin regulation. Science. 389(6758). eadt2781–eadt2781. 2 indexed citations

2.

Schiroli, Giulia, Vinay K. Kartha, Fabiana M. Duarte, et al.. (2024). Cell of origin epigenetic priming determines susceptibility to Tet2 mutation. Nature Communications. 15(1). 4325–4325. 3 indexed citations

3.

Mangiameli, Sarah, et al.. (2023). Photoselective sequencing: microscopically guided genomic measurements with subcellular resolution. Nature Methods. 20(5). 686–694. 7 indexed citations

4.

Kartha, Vinay K., Fabiana M. Duarte, Yan Hu, et al.. (2022). Functional inference of gene regulation using single-cell multi-omics. Cell Genomics. 2(9). 100166–100166. 101 indexed citations

5.

Payne, Andrew C., Zachary Chiang, Paul Reginato, et al.. (2021). In situ genome sequencing resolves DNA sequence and structure in intact biological samples. Science. 371(6532). 141 indexed citations

6.

Zhao, Tongtong, Zachary Chiang, Julia W. Morriss, et al.. (2021). Spatial genomics enables multi-modal study of clonal heterogeneity in tissues. Nature. 601(7891). 85–91. 155 indexed citations

7.

Bates, C.E., et al.. (2021). Proximal-end bias from in-vitro reconstituted nucleosomes and the result on downstream data analysis. PLoS ONE. 16(10). e0258737–e0258737. 1 indexed citations

8.

Liberman, Noa, Zach Klapholz O’Brown, Andrew Earl, et al.. (2020). N6-adenosine methylation of ribosomal RNA affects lipid oxidation and stress resistance. Science Advances. 6(17). eaaz4370–eaaz4370. 40 indexed citations

9.

Ma, Sai, Bing Zhang, Lindsay M. LaFave, et al.. (2020). Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin. Cell. 183(4). 1103–1116.e20. 579 indexed citations breakdown →

10.

He, Yongfeng, Erika Hooker, Eun‐Jeong Yu, et al.. (2018). Androgen signaling is essential for development of prostate cancer initiated from prostatic basal cells. Oncogene. 38(13). 2337–2350. 14 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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