JL Weissman

883 total citations
24 papers, 422 citations indexed

About

JL Weissman is a scholar working on Molecular Biology, Ecology and Genetics. According to data from OpenAlex, JL Weissman has authored 24 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 15 papers in Ecology and 5 papers in Genetics. Recurrent topics in JL Weissman's work include Microbial Community Ecology and Physiology (12 papers), Genomics and Phylogenetic Studies (7 papers) and CRISPR and Genetic Engineering (6 papers). JL Weissman is often cited by papers focused on Microbial Community Ecology and Physiology (12 papers), Genomics and Phylogenetic Studies (7 papers) and CRISPR and Genetic Engineering (6 papers). JL Weissman collaborates with scholars based in United States, United Kingdom and Canada. JL Weissman's co-authors include Jed A. Fuhrman, Shengwei Hou, William F. Fagan, Philip L. F. Johnson, Philip L. Johnson, Edze R. Westra, Rodolphe Barrangou, Sylvain Moineau, Bruce R. Levin and Arlin Stoltzfus and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and PLoS Biology.

In The Last Decade

JL Weissman

20 papers receiving 420 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
JL Weissman United States	9	265	230	97	44	31	24	422
Gabriela Olmedo‐Álvarez Mexico	12	304 1.1×	271 1.2×	106 1.1×	88 2.0×	21 0.7×	37	532
William R. Shoemaker United States	10	272 1.0×	157 0.7×	140 1.4×	51 1.2×	14 0.5×	19	476
Nora Connor United States	4	255 1.0×	210 0.9×	70 0.7×	71 1.6×	21 0.7×	9	408
Stephan Köstlbacher Austria	15	244 0.9×	210 0.9×	56 0.6×	95 2.2×	32 1.0×	23	540
Sonia Dávila‐Ramos Mexico	11	179 0.7×	139 0.6×	70 0.7×	67 1.5×	32 1.0×	23	353
Chris Hemmerich United States	12	206 0.8×	85 0.4×	43 0.4×	47 1.1×	30 1.0×	14	440
Natalie A. Sawaya United States	7	345 1.3×	629 2.7×	37 0.4×	136 3.1×	49 1.6×	8	701
Francesco Rubino Italy	10	309 1.2×	233 1.0×	56 0.6×	32 0.7×	13 0.4×	27	629
Nana Y. D. Ankrah United States	12	161 0.6×	195 0.8×	46 0.5×	87 2.0×	21 0.7×	16	411
Tyler C. Bradley United States	4	126 0.5×	79 0.3×	61 0.6×	81 1.8×	17 0.5×	5	364

Countries citing papers authored by JL Weissman

Since Specialization

Citations

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

Fields of papers citing papers by JL Weissman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of JL Weissman

This figure shows the co-authorship network connecting the top 25 collaborators of JL Weissman. A scholar is included among the top collaborators of JL Weissman 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 JL Weissman. JL Weissman 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

Weissman, JL, Shengwei Hou, Yi‐Chun Yeh, et al.. (2025). Phylogenetic proximity is a key driver of temporal succession of marine giant viruses in a five-year metagenomic time-series. ISME Communications. 5(1). ycaf217–ycaf217.

Buchanan, Pearse, et al.. (2025). Oxygen intrusions sustain aerobic nitrite-oxidizing bacteria in anoxic marine zones. Science. 388(6751). 1069–1074. 2 indexed citations

Zakem, Emily J., Jesse McNichol, JL Weissman, et al.. (2025). Functional biogeography of marine microbial heterotrophs. Science. 388(6749). eado5323–eado5323.

Osburn, Ernest D., JL Weissman, Michael S. Strickland, et al.. (2025). Relative abundances of bacterial phyla are strong indicators of community-scale microbial growth rates in soil. Environmental Microbiome. 20(1). 131–131.

Xu, Liang, Emily J. Zakem, & JL Weissman. (2025). Improved maximum growth rate prediction from microbial genomes by integrating phylogenetic information. PubMed. 16(1). 4256–4256. 2 indexed citations

Weissman, JL, et al.. (2024). Ecological drivers of CRISPR immune systems. mSystems. 9(12). e0056824–e0056824. 5 indexed citations

Weissman, JL, Anna C. Fagre, Steven A. Frese, et al.. (2024). Queer- and trans-inclusive faculty hiring—A call for change. PLoS Biology. 22(11). e3002919–e3002919. 2 indexed citations

Yeh, Yi‐Chun, et al.. (2023). Symbiotic UCYN-A strains co-occurred with El Niño, relaxed upwelling, and varied eukaryotes over 10 years off Southern California. ISME Communications. 3(1). 63–63. 5 indexed citations

Ellenbogen, Jared, Steve Frolking, Jessica G. Ernakovich, et al.. (2023). What is microbial dormancy?. Trends in Microbiology. 32(2). 142–150. 38 indexed citations

10.

Cram, Jacob A., et al.. (2022). NetGAM: Using generalized additive models to improve the predictive power of ecological network analyses constructed using time-series data. ISME Communications. 2(1). 23–23. 4 indexed citations

11.

Wang, Wenxiu, JL Weissman, Yongyu Zhang, et al.. (2022). Size-fractionated microbiome observed during an eight-month long sampling in Jiaozhou Bay and the Yellow Sea. Scientific Data. 9(1). 605–605. 1 indexed citations

12.

Weissman, JL, Samantha Bolten, Peter Thielen, et al.. (2021). Exploring the functional composition of the human microbiome using a hand-curated microbial trait database. BMC Bioinformatics. 22(1). 306–306. 6 indexed citations

13.

Weissman, JL, Shengwei Hou, & Jed A. Fuhrman. (2021). Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns. Proceedings of the National Academy of Sciences. 118(12). 163 indexed citations

14.

Weissman, JL, et al.. (2021). Immune lag is a major cost of prokaryotic adaptive immunity during viral outbreaks. Proceedings of the Royal Society B Biological Sciences. 288(1961). 20211555–20211555. 6 indexed citations

15.

Weissman, JL, Arlin Stoltzfus, Edze R. Westra, & Philip L. F. Johnson. (2020). Avoidance of Self during CRISPR Immunization. Trends in Microbiology. 28(7). 543–553. 18 indexed citations

16.

Weissman, JL, et al.. (2019). Visualization and prediction of CRISPR incidence in microbial trait-space to identify drivers of antiviral immune strategy. The ISME Journal. 13(10). 2589–2602. 30 indexed citations

17.

Weissman, JL, William F. Fagan, & Philip L. F. Johnson. (2019). Linking high GC content to the repair of double strand breaks in prokaryotic genomes. PLoS Genetics. 15(11). e1008493–e1008493. 41 indexed citations

18.

Bewick, Sharon, Eliezer Gurarie, JL Weissman, et al.. (2019). Trait-based analysis of the human skin microbiome. Microbiome. 7(1). 101–101. 26 indexed citations

19.

Weissman, JL, Rodolphe Barrangou, Sylvain Moineau, et al.. (2018). Immune loss as a driver of coexistence during host-phage coevolution. The ISME Journal. 12(2). 585–597. 42 indexed citations

20.

Weissman, JL, William F. Fagan, & Philip L. Johnson. (2018). Selective Maintenance of Multiple CRISPR Arrays Across Prokaryotes. The CRISPR Journal. 1(6). 405–413. 15 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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