Joshua S. Bloom

4.0k total citations
43 papers, 2.1k citations indexed

About

Joshua S. Bloom is a scholar working on Molecular Biology, Genetics and Food Science. According to data from OpenAlex, Joshua S. Bloom has authored 43 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 21 papers in Genetics and 6 papers in Food Science. Recurrent topics in Joshua S. Bloom's work include Genetic Mapping and Diversity in Plants and Animals (19 papers), Fungal and yeast genetics research (13 papers) and Bioinformatics and Genomic Networks (7 papers). Joshua S. Bloom is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (19 papers), Fungal and yeast genetics research (13 papers) and Bioinformatics and Genomic Networks (7 papers). Joshua S. Bloom collaborates with scholars based in United States, Israel and United Kingdom. Joshua S. Bloom's co-authors include Leonid Kruglyak, Meru J. Sadhu, Erik C. Andersen, Justin Gerke, Ian M. Ehrenreich, Frank W. Albert, Wesley T. Loo, Laura Day, Sebastian Treusch and Rajarshi Ghosh and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Joshua S. Bloom

42 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Joshua S. Bloom United States	25	1.3k	986	426	402	146	43	2.1k
Darren Platt United States	12	1.4k 1.1×	383 0.4×	402 0.9×	195 0.5×	117 0.8×	22	2.2k
Todd Harris United States	13	1.7k 1.3×	353 0.4×	378 0.9×	520 1.3×	48 0.3×	16	2.4k
Sasha F. Levy United States	22	1.4k 1.1×	795 0.8×	79 0.2×	172 0.4×	67 0.5×	34	1.8k
Patrick T. McGrath United States	22	1.1k 0.8×	998 1.0×	650 1.5×	219 0.5×	21 0.1×	42	2.1k
Joost A. G. Riksen Netherlands	21	528 0.4×	633 0.6×	734 1.7×	308 0.8×	20 0.1×	44	1.4k
Ritsert C. Jansen Netherlands	31	2.0k 1.5×	1.2k 1.2×	79 0.2×	1.5k 3.8×	68 0.5×	64	3.5k
Gudrun A. Brockmann Germany	30	844 0.6×	1.9k 1.9×	49 0.1×	365 0.9×	182 1.2×	173	3.2k
Cristian I. Castillo-Davis United States	11	1.1k 0.8×	640 0.6×	68 0.2×	354 0.9×	56 0.4×	11	1.7k
Sarah E. Hall United States	27	1.1k 0.8×	417 0.4×	211 0.5×	548 1.4×	31 0.2×	45	2.8k

Countries citing papers authored by Joshua S. Bloom

Since Specialization

Citations

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

Fields of papers citing papers by Joshua S. Bloom

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joshua S. Bloom. 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 Joshua S. Bloom. The network helps show where Joshua S. Bloom may publish in the future.

Co-authorship network of co-authors of Joshua S. Bloom

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

All Works

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20 of 20 papers shown

Boocock, James, et al.. (2025). Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction. eLife. 13. 1 indexed citations

Zahm, Adam M., William Owens, Joshua S. Bloom, et al.. (2024). A massively parallel reporter assay library to screen short synthetic promoters in mammalian cells. Nature Communications. 15(1). 10353–10353. 6 indexed citations

Boocock, James, et al.. (2024). Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction. eLife. 13. 1 indexed citations

Howard, Conor J, Nathan S. Abell, Beatriz A. Osuna, et al.. (2024). High-resolution deep mutational scanning of the melanocortin-4 receptor enables target characterization for drug discovery. eLife. 13. 3 indexed citations

Chambers, Michael, et al.. (2023). Highly complete long-read genomes reveal pangenomic variation underlying yeast phenotypic diversity. Genome Research. 33(5). 729–740. 9 indexed citations

Schubert, Olga T., Joshua S. Bloom, Meru J. Sadhu, & Leonid Kruglyak. (2022). Genome-wide base editor screen identifies regulators of protein abundance in yeast. eLife. 11. 14 indexed citations

Boocock, James, Meru J. Sadhu, Arun Durvasula, Joshua S. Bloom, & Leonid Kruglyak. (2021). Ancient balancing selection maintains incompatible versions of the galactose pathway in yeast. Science. 371(6527). 415–419. 26 indexed citations

Ben‐David, Eyal, James Boocock, Longhua Guo, et al.. (2021). Whole-organism eQTL mapping at cellular resolution with single-cell sequencing. eLife. 10. 26 indexed citations

Guo, Longhua, Joshua S. Bloom, Elaine Huang, et al.. (2021). Genetics of white color and iridophoroma in “Lemon Frost” leopard geckos. PLoS Genetics. 17(6). e1009580–e1009580. 12 indexed citations

10.

Rau, Christoph, Natalia M. Gonzales, Joshua S. Bloom, et al.. (2020). Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”. PLoS Genetics. 16(10). e1009165–e1009165. 4 indexed citations

11.

Jones, Eric M., Daniel Cancilla, Nathan B. Lubock, et al.. (2019). A Scalable, Multiplexed Assay for Decoding GPCR-Ligand Interactions with RNA Sequencing. Cell Systems. 8(3). 254–260.e6. 26 indexed citations

12.

Bloom, Joshua S., et al.. (2018). The Genetic Basis of Mutation Rate Variation in Yeast. Genetics. 211(2). 731–740. 35 indexed citations

13.

Albert, Frank W., Joshua S. Bloom, Jake J. Siegel, Laura Day, & Leonid Kruglyak. (2018). Genetics of trans-regulatory variation in gene expression. eLife. 7. 103 indexed citations

14.

Sadhu, Meru J., Joshua S. Bloom, Laura Day, et al.. (2018). Highly parallel genome variant engineering with CRISPR–Cas9. Nature Genetics. 50(4). 510–514. 57 indexed citations

15.

Jerison, Elizabeth R., Sergey Kryazhimskiy, James K. Mitchell, et al.. (2017). Genetic variation in adaptability and pleiotropy in budding yeast. eLife. 6. 49 indexed citations

16.

Forsberg, Simon K. G., Joshua S. Bloom, Meru J. Sadhu, Leonid Kruglyak, & Örjan Carlborg. (2017). Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast. Nature Genetics. 49(4). 497–503. 85 indexed citations

17.

Sadhu, Meru J., Joshua S. Bloom, Laura Day, & Leonid Kruglyak. (2016). CRISPR-directed mitotic recombination enables genetic mapping without crosses. Science. 352(6289). 1113–1116. 68 indexed citations

18.

Ghosh, Rajarshi, Joshua S. Bloom, Molly Schumer, et al.. (2015). Genetics of Intraspecies Variation in Avoidance Behavior Induced by a Thermal Stimulus in Caenorhabditis elegans. Genetics. 200(4). 1327–1339. 5 indexed citations

19.

Bloom, Joshua S., et al.. (2013). Finding the sources of missing heritability in a yeast cross. Nature. 494(7436). 234–237. 302 indexed citations

20.

Plazas-Mayorca, Mariana D., Joshua S. Bloom, Ulrike Zeißler, et al.. (2010). Quantitative proteomics reveals direct and indirect alterations in the histone code following methyltransferase knockdown. Molecular BioSystems. 6(9). 1719–1729. 29 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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