Joel D. Nelson

1.3k total citations · 1 hit paper
9 papers, 1.1k citations indexed

About

Joel D. Nelson is a scholar working on Molecular Biology, Physiology and Surgery. According to data from OpenAlex, Joel D. Nelson has authored 9 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Physiology and 1 paper in Surgery. Recurrent topics in Joel D. Nelson's work include Genomics and Chromatin Dynamics (6 papers), RNA Research and Splicing (5 papers) and RNA and protein synthesis mechanisms (3 papers). Joel D. Nelson is often cited by papers focused on Genomics and Chromatin Dynamics (6 papers), RNA Research and Splicing (5 papers) and RNA and protein synthesis mechanisms (3 papers). Joel D. Nelson collaborates with scholars based in United States. Joel D. Nelson's co-authors include Karol Bomsztyk, Oleg Denisenko, David G. Castner, Renee Leboeuf, Anuradha Vivekanandan‐Giri, Kelly D. Smith, Gordon J. Lithgow, Karin Bornfeldt, Harald Frankowski and Patricia Spilman and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Diabetes.

In The Last Decade

Joel D. Nelson

9 papers receiving 1.1k citations

Hit Papers

Protocol for the fast chromatin immunoprecipitation (ChIP... 2006 2026 2012 2019 2006 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joel D. Nelson United States 8 851 141 127 121 94 9 1.1k
Trent Su United States 19 835 1.0× 188 1.3× 118 0.9× 108 0.9× 125 1.3× 28 1.3k
Jukka Kallijärvi Finland 19 753 0.9× 134 1.0× 161 1.3× 84 0.7× 126 1.3× 41 1.1k
X-J Yang China 10 1.1k 1.3× 143 1.0× 71 0.6× 199 1.6× 158 1.7× 19 1.3k
Emanuela Tumini Spain 12 961 1.1× 117 0.8× 83 0.7× 177 1.5× 154 1.6× 20 1.2k
Maja Hemmings-Mieszczak Switzerland 13 888 1.0× 81 0.6× 111 0.9× 77 0.6× 98 1.0× 14 1.2k
Loris Bernard Italy 14 739 0.9× 149 1.1× 57 0.4× 147 1.2× 210 2.2× 23 1.1k
Valentina Iadevaia United Kingdom 19 879 1.0× 130 0.9× 90 0.7× 85 0.7× 55 0.6× 31 1.2k
Prashant K. Srivastava United Kingdom 18 703 0.8× 249 1.8× 145 1.1× 71 0.6× 119 1.3× 51 1.1k
R Misra United States 9 544 0.6× 63 0.4× 89 0.7× 93 0.8× 79 0.8× 17 829
Archana Dhasarathy United States 18 799 0.9× 142 1.0× 63 0.5× 229 1.9× 137 1.5× 31 1.0k

Countries citing papers authored by Joel D. Nelson

Since Specialization
Citations

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

Fields of papers citing papers by Joel D. Nelson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joel D. Nelson. 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 Joel D. Nelson. The network helps show where Joel D. Nelson may publish in the future.

Co-authorship network of co-authors of Joel D. Nelson

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

All Works

9 of 9 papers shown
1.
Rubinow, Katya B., Valerie Wall, Joel D. Nelson, et al.. (2013). Acyl-CoA Synthetase 1 Is Induced by Gram-negative Bacteria and Lipopolysaccharide and Is Required for Phospholipid Turnover in Stimulated Macrophages. Journal of Biological Chemistry. 288(14). 9957–9970. 57 indexed citations
2.
Frankowski, Harald, Silvestre Alavez, Patricia Spilman, et al.. (2013). Dimethyl sulfoxide and dimethyl formamide increase lifespan of C. elegans in liquid. Mechanisms of Ageing and Development. 134(3-4). 69–78. 36 indexed citations
3.
Nelson, Joel D., Oleg Denisenko, & Karol Bomsztyk. (2010). Profiling RNA Polymerase II Using the Fast Chromatin Immunoprecipitation Method. Methods in molecular biology. 219–234. 6 indexed citations
4.
Nelson, Joel D., Renee Leboeuf, & Karol Bomsztyk. (2010). Direct Recruitment of Insulin Receptor and ERK Signaling Cascade to Insulin-Inducible Gene Loci. Diabetes. 60(1). 127–137. 33 indexed citations
5.
Nelson, Joel D., Oleg Denisenko, & Karol Bomsztyk. (2009). The Fast Chromatin Immunoprecipitation Method. Methods in molecular biology. 567. 45–57. 25 indexed citations
6.
Nelson, Joel D., et al.. (2008). Transcription of laminin γ1 chain gene in rat mesangial cells: constitutive and inducible RNA polymerase II recruitment and chromatin states. American Journal of Physiology-Renal Physiology. 294(3). F525–F533. 12 indexed citations
7.
Nelson, Joel D., et al.. (2008). Microplate-based chromatin immunoprecipitation method, Matrix ChIP: a platform to study signaling of complex genomic events. Nucleic Acids Research. 36(3). e17–e17. 71 indexed citations
8.
Nelson, Joel D., Oleg Denisenko, & Karol Bomsztyk. (2006). Protocol for the fast chromatin immunoprecipitation (ChIP) method. Nature Protocols. 1(1). 179–185. 647 indexed citations breakdown →
9.
Nelson, Joel D.. (2006). Fast chromatin immunoprecipitation assay. Nucleic Acids Research. 34(1). e2–e2. 197 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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