Brian Cleary

3.1k total citations · 3 hit papers
17 papers, 1.2k citations indexed

About

Brian Cleary is a scholar working on Molecular Biology, Biophysics and Biomedical Engineering. According to data from OpenAlex, Brian Cleary has authored 17 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 4 papers in Biophysics and 3 papers in Biomedical Engineering. Recurrent topics in Brian Cleary's work include Single-cell and spatial transcriptomics (9 papers), CRISPR and Genetic Engineering (4 papers) and Cell Image Analysis Techniques (3 papers). Brian Cleary is often cited by papers focused on Single-cell and spatial transcriptomics (9 papers), CRISPR and Genetic Engineering (4 papers) and Cell Image Analysis Techniques (3 papers). Brian Cleary collaborates with scholars based in United States, Israel and Gambia. Brian Cleary's co-authors include Eric S. Lander, Aviv Regev, Sharon R. Grossman, Rockwell Anyoha, Mathias Munschauer, Michael Kane, Elizabeth M. Perez, Charles P. Fulco, Glen Munson and J Engreitz and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Brian Cleary

17 papers receiving 1.2k 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.

Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming

2019 409 citations Geoffrey Schiebinger, Jian Shu et al. Cell profile →
Systematic mapping of functional enhancer–promoter connections with CRISPR interference

2016 390 citations Charles P. Fulco, Mathias Munschauer et al. Science profile →
Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits

2025 18 citations Loïc Binan, Aiping Jiang 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
Brian Cleary United States	11	973	119	118	117	112	17	1.2k
Mor Nitzan Israel	17	675 0.7×	80 0.7×	137 1.2×	84 0.7×	92 0.8×	33	1.3k
Miriam V. Gutschow United States	10	954 1.0×	119 1.0×	202 1.7×	74 0.6×	79 0.7×	12	1.3k
Florian Hahne United States	10	1.1k 1.2×	71 0.6×	201 1.7×	169 1.4×	153 1.4×	17	1.6k
Grégoire Pau France	11	904 0.9×	60 0.5×	174 1.5×	190 1.6×	122 1.1×	19	1.5k
Jayodita C. Sanghvi United States	5	905 0.9×	114 1.0×	188 1.6×	80 0.7×	68 0.6×	8	1.1k
Tatyana Goldberg Germany	15	1.1k 1.1×	93 0.8×	186 1.6×	50 0.4×	102 0.9×	22	1.7k
Zhongying Zhao Hong Kong	26	955 1.0×	140 1.2×	270 2.3×	128 1.1×	96 0.9×	86	1.9k
Derek N. Macklin United States	7	1.1k 1.1×	86 0.7×	173 1.5×	322 2.8×	63 0.6×	8	1.5k
Yihan Lin China	13	726 0.7×	40 0.3×	208 1.8×	83 0.7×	57 0.5×	36	975
Michael J. Lawson United States	13	1.5k 1.5×	63 0.5×	200 1.7×	313 2.7×	172 1.5×	14	1.8k

Countries citing papers authored by Brian Cleary

Since Specialization

Citations

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

Fields of papers citing papers by Brian Cleary

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Cleary

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

All Works

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17 of 17 papers shown

Nelson, Jack, Luhan T. Zhou, Alex K. Shalek, et al.. (2025). Single-cell and spatiotemporal profile of ovulation in the mouse ovary. PLoS Biology. 23(6). e3003193–e3003193. 2 indexed citations

Binan, Loïc, Aiping Jiang, Vera Valakh, et al.. (2025). Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits. Cell. 188(8). 2141–2158.e18. 18 indexed citations breakdown →

Bolten, John, et al.. (2024). Deep Convolutional LSTM for improved flash flood prediction. Frontiers in Water. 6. 10 indexed citations

Binan, Loïc, et al.. (2023). Optimization-based decoding of Imaging Spatial Transcriptomics data. Bioinformatics. 39(6). 2 indexed citations

Yao, Douglas, Loïc Binan, Brooke Simonton, et al.. (2023). Scalable genetic screening for regulatory circuits using compressed Perturb-seq. Nature Biotechnology. 42(8). 1282–1295. 37 indexed citations

Gupta, Anika, Jorge D. Martin-Rufino, Thouis R. Jones, et al.. (2022). Inferring gene regulation from stochastic transcriptional variation across single cells at steady state. Proceedings of the National Academy of Sciences. 119(34). e2207392119–e2207392119. 18 indexed citations

Hong, David, Rounak Dey, Xihong Lin, Brian Cleary, & Edgar Dobriban. (2022). Group testing via hypergraph factorization applied to COVID-19. Nature Communications. 13(1). 1837–1837. 4 indexed citations

Einav, Tal & Brian Cleary. (2022). Extrapolating missing antibody-virus measurements across serological studies. Cell Systems. 13(7). 561–573.e5. 4 indexed citations

Cleary, Brian, et al.. (2022). Deep Unrolled Recovery in Sparse Biological Imaging: Achieving fast, accurate results. IEEE Signal Processing Magazine. 39(2). 45–57. 12 indexed citations

10.

Cleary, Brian, Brooke Simonton, Evan Murray, et al.. (2021). Compressed sensing for highly efficient imaging transcriptomics. Nature Biotechnology. 39(8). 936–942. 27 indexed citations

11.

Cleary, Brian, James A. Hay, Brendan Blumenstiel, et al.. (2021). Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings. Science Translational Medicine. 13(589). 30 indexed citations

12.

Cleary, Brian, et al.. (2021). Sparse Recovery Of Imaging Transcriptomics Data. 280. 802–806. 3 indexed citations

13.

Schiebinger, Geoffrey, Jian Shu, Marcin Tabaka, et al.. (2019). Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming. Cell. 176(4). 928–943.e22. 409 indexed citations breakdown →

14.

Martín‐Platero, Antonio M., Brian Cleary, Kathryn M. Kauffman, et al.. (2018). High resolution time series reveals cohesive but short-lived communities in coastal plankton. Nature Communications. 9(1). 266–266. 98 indexed citations

15.

Cleary, Brian, et al.. (2017). Efficient Generation of Transcriptomic Profiles by Random Composite Measurements. Cell. 171(6). 1424–1436.e18. 65 indexed citations

16.

Fulco, Charles P., Mathias Munschauer, Rockwell Anyoha, et al.. (2016). Systematic mapping of functional enhancer–promoter connections with CRISPR interference. Science. 354(6313). 769–773. 390 indexed citations breakdown →

17.

Cleary, Brian, Ilana Brito, Katherine Huang, et al.. (2015). Detection of low-abundance bacterial strains in metagenomic datasets by eigengenome partitioning. Nature Biotechnology. 33(10). 1053–1060. 91 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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