Jonathan Scheiman

7.5k total citations · 3 hit papers
8 papers, 3.0k citations indexed

About

Jonathan Scheiman is a scholar working on Molecular Biology, Physiology and Immunology and Allergy. According to data from OpenAlex, Jonathan Scheiman has authored 8 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Physiology and 2 papers in Immunology and Allergy. Recurrent topics in Jonathan Scheiman's work include RNA Research and Splicing (3 papers), Molecular Biology Techniques and Applications (2 papers) and Cell Adhesion Molecules Research (2 papers). Jonathan Scheiman is often cited by papers focused on RNA Research and Splicing (3 papers), Molecular Biology Techniques and Applications (2 papers) and Cell Adhesion Molecules Research (2 papers). Jonathan Scheiman collaborates with scholars based in United States, Italy and Canada. Jonathan Scheiman's co-authors include George M. Church, John Aach, Brian M. Turczyk, Je Hyuk Lee, Evan R Daugharthy, Thomas C. Ferrante, Joyce Yang, Reza Kalhor, Noah Davidsohn and Christopher D. Guzman and has published in prestigious journals such as Science, Nature Medicine and Nature Methods.

In The Last Decade

Jonathan Scheiman

8 papers receiving 2.9k citations

Hit Papers

Highly efficient Cas9-mediated transcriptional programming 2014 2026 2018 2022 2015 2014 2019 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Scheiman United States 7 2.6k 362 305 246 219 8 3.0k
Saori Kashiwagi Japan 15 1.6k 0.6× 267 0.7× 125 0.4× 268 1.1× 304 1.4× 39 2.4k
Malin Åkerfelt Finland 17 1.7k 0.7× 208 0.6× 136 0.4× 139 0.6× 56 0.3× 25 2.3k
Yanxia Liu United States 24 2.9k 1.1× 218 0.6× 153 0.5× 327 1.3× 35 0.2× 35 3.7k
Akiko Fujita Japan 21 2.1k 0.8× 238 0.7× 128 0.4× 209 0.8× 166 0.8× 80 3.8k
Mary McKee United States 34 2.3k 0.9× 489 1.4× 312 1.0× 288 1.2× 58 0.3× 51 4.0k
Vincent L. Butty United States 25 1.8k 0.7× 157 0.4× 714 2.3× 303 1.2× 30 0.1× 41 2.7k
Michael E. Rothenberg United States 19 1.4k 0.5× 76 0.2× 249 0.8× 257 1.0× 70 0.3× 35 2.2k
Katherine Donovan United States 8 3.0k 1.2× 83 0.2× 195 0.6× 492 2.0× 44 0.2× 15 3.6k
Joep Beumer Netherlands 21 1.2k 0.5× 177 0.5× 202 0.7× 511 2.1× 78 0.4× 30 2.7k
Mo R. Ebrahimkhani United States 30 1.5k 0.6× 188 0.5× 98 0.3× 247 1.0× 33 0.2× 54 2.6k

Countries citing papers authored by Jonathan Scheiman

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Scheiman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Scheiman

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

All Works

8 of 8 papers shown
1.
Bongiovanni, Tindaro, Marina Santiago, Jonathan Scheiman, et al.. (2025). A Lactobacillus consortium provides insights into the sleep-exercise-microbiome nexus in proof of concept studies of elite athletes and in the general population. Microbiome. 13(1). 1–1. 5 indexed citations
2.
Santiago, Marina, et al.. (2023). Impact of probiotic Veillonella atypica FB0054 supplementation on anaerobic capacity and lactate. iScience. 27(1). 108643–108643. 16 indexed citations
3.
Scheiman, Jonathan, Jacob M. Luber, Theodore A. Chavkin, et al.. (2019). Meta-omics analysis of elite athletes identifies a performance-enhancing microbe that functions via lactate metabolism. Nature Medicine. 25(7). 1104–1109. 579 indexed citations breakdown →
4.
Lee, Je Hyuk, Evan R Daugharthy, Jonathan Scheiman, et al.. (2015). Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues. Nature Protocols. 10(3). 442–458. 387 indexed citations
5.
Chavez, Alejandro, Jonathan Scheiman, Suhani Vora, et al.. (2015). Highly efficient Cas9-mediated transcriptional programming. Nature Methods. 12(4). 326–328. 1183 indexed citations breakdown →
6.
Lee, Je Hyuk, Evan R Daugharthy, Jonathan Scheiman, et al.. (2014). Highly Multiplexed Subcellular RNA Sequencing in Situ. Science. 343(6177). 1360–1363. 693 indexed citations breakdown →
7.
Scheiman, Jonathan, et al.. (2010). Extraribosomal functions associated with the C terminus of the 37/67 kDa laminin receptor are required for maintaining cell viability. Cell Death and Disease. 1(5). e42–e42. 34 indexed citations
8.
Scheiman, Jonathan, Jen‐Chieh Tseng, Yun Zheng, & Daniel Meruelo. (2009). Multiple Functions of the 37/67-kd Laminin Receptor Make It a Suitable Target for Novel Cancer Gene Therapy. Molecular Therapy. 18(1). 63–74. 62 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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