David Sturgill

10.1k total citations · 1 hit paper
37 papers, 2.9k citations indexed

About

David Sturgill is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, David Sturgill has authored 37 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 10 papers in Genetics and 7 papers in Plant Science. Recurrent topics in David Sturgill's work include RNA and protein synthesis mechanisms (12 papers), Genomics and Chromatin Dynamics (10 papers) and RNA modifications and cancer (9 papers). David Sturgill is often cited by papers focused on RNA and protein synthesis mechanisms (12 papers), Genomics and Chromatin Dynamics (10 papers) and RNA modifications and cancer (9 papers). David Sturgill collaborates with scholars based in United States, France and Malaysia. David Sturgill's co-authors include Michael Parisi, Brian Oliver, Brian Oliver, Yu Zhang, Shalini Oberdoerffer, Miroslav Dundr, Iain A. Sawyer, Daniel Arango, Sudhir Kumar and Kyster K. Nanan and has published in prestigious journals such as Nature, Cell and Nucleic Acids Research.

In The Last Decade

David Sturgill

36 papers receiving 2.9k citations

Hit Papers

Acetylation of Cytidine in mRNA Promotes Translation Effi... 2018 2026 2020 2023 2018 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Sturgill United States 23 2.1k 1.1k 398 331 300 37 2.9k
Hugues Parrinello France 25 1.5k 0.7× 694 0.7× 526 1.3× 123 0.4× 390 1.3× 49 2.4k
Matthias Soller United Kingdom 30 2.6k 1.3× 967 0.9× 483 1.2× 800 2.4× 569 1.9× 79 4.0k
Melissa M. Harrison United States 29 3.1k 1.5× 579 0.6× 674 1.7× 138 0.4× 88 0.3× 53 3.7k
Yavuz Ariyürek Netherlands 25 1.8k 0.9× 530 0.5× 380 1.0× 346 1.0× 87 0.3× 40 2.5k
Fugaku Aoki Japan 34 3.0k 1.5× 746 0.7× 289 0.7× 183 0.6× 55 0.2× 119 4.0k
Brian Oliver United States 33 2.7k 1.3× 2.1k 2.0× 915 2.3× 205 0.6× 579 1.9× 84 4.5k
Michael T. Marr United States 25 2.6k 1.3× 949 0.9× 236 0.6× 190 0.6× 45 0.1× 41 3.2k
Ji‐Long Liu China 39 4.0k 2.0× 469 0.4× 291 0.7× 251 0.8× 60 0.2× 132 4.7k
Tessa G. Montague United States 12 2.8k 1.4× 570 0.5× 331 0.8× 194 0.6× 59 0.2× 16 3.5k
John A. McNeil United States 18 2.3k 1.1× 1.0k 1.0× 488 1.2× 320 1.0× 80 0.3× 24 3.1k

Countries citing papers authored by David Sturgill

Since Specialization
Citations

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

Fields of papers citing papers by David Sturgill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Sturgill

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

All Works

20 of 20 papers shown
1.
Beiki, Hamid, et al.. (2024). Detection of ac4C in human mRNA is preserved upon data reassessment. Molecular Cell. 84(8). 1611–1625.e3. 13 indexed citations
2.
Arango, Daniel, David Sturgill, Renbin Yang, et al.. (2022). Direct epitranscriptomic regulation of mammalian translation initiation through N4-acetylcytidine. Molecular Cell. 82(15). 2797–2814.e11. 102 indexed citations
3.
Sturgill, David, Daniel Arango, & Shalini Oberdoerffer. (2022). Protocol for base resolution mapping of ac4C using RedaC:T-seq. STAR Protocols. 3(4). 101858–101858. 14 indexed citations
4.
Heard, Édith, Alexander D. Johnson, Jan O. Korbel, et al.. (2021). The X Chromosome from Telomere to Telomere: Key Achievements and Future Opportunities. PubMed. 10. 63–63. 1 indexed citations
5.
Nanan, Kyster K., David Sturgill, Morgan Thénoz, et al.. (2019). TET-Catalyzed 5-Carboxylcytosine Promotes CTCF Binding to Suboptimal Sequences Genome-wide. iScience. 19. 326–339. 20 indexed citations
6.
Sturgill, David, et al.. (2018). HJURP antagonizes CENP-A mislocalization driven by the H3.3 chaperones HIRA and DAXX. PLoS ONE. 13(10). e0205948–e0205948. 38 indexed citations
7.
Arango, Daniel, David Sturgill, Najwa Alhusaini, et al.. (2018). Acetylation of Cytidine in mRNA Promotes Translation Efficiency. Cell. 175(7). 1872–1886.e24. 566 indexed citations breakdown →
8.
Nanan, Kyster K., et al.. (2017). Independence between pre-mRNA splicing and DNA methylation in an isogenic minigene resource. Nucleic Acids Research. 45(22). 12780–12797. 2 indexed citations
9.
Raub, Stephan, et al.. (2016). Linking Genes and Brain Development of Honeybee Workers: A Whole-Transcriptome Approach. PLoS ONE. 11(8). e0157980–e0157980. 20 indexed citations
10.
Quénet, Delphine, David Sturgill, & Yamini Dalal. (2016). Identifying Centromeric RNAs Involved in Histone Dynamics In Vivo. Methods in enzymology on CD-ROM/Methods in enzymology. 573. 445–466. 1 indexed citations
11.
Wang, Qiuyan, Iain A. Sawyer, Myong‐Hee Sung, et al.. (2016). Cajal bodies are linked to genome conformation. Nature Communications. 7(1). 10966–10966. 125 indexed citations
12.
Kim, Jeongkyu, David Sturgill, Andy D. Tran, David Sinclair, & Philipp Oberdoerffer. (2015). Controlled DNA double-strand break induction in mice reveals post-damage transcriptome stability. Nucleic Acids Research. 44(7). e64–e64. 48 indexed citations
13.
Clough, Emily, Erin Jimenez, Yoo-Ah Kim, et al.. (2014). Sex- and Tissue-Specific Functions of Drosophila Doublesex Transcription Factor Target Genes. Developmental Cell. 31(6). 761–773. 99 indexed citations
14.
Parisi, Michael, Vaijayanti Gupta, David Sturgill, et al.. (2010). Germline-dependent gene expression in distant non-gonadal somatic tissues of Drosophila. BMC Genomics. 11(1). 346–346. 29 indexed citations
15.
Larracuente, Amanda M., Timothy B. Sackton, Anthony J. Greenberg, et al.. (2008). Evolution of protein-coding genes in Drosophila. Trends in Genetics. 24(3). 114–123. 208 indexed citations
16.
Sturgill, David, Yu Zhang, Michael Parisi, & Brian Oliver. (2007). Demasculinization of X chromosomes in the Drosophila genus. Nature. 450(7167). 238–241. 187 indexed citations
17.
Zhang, Yu, David Sturgill, Michael Parisi, Sudhir Kumar, & Brian Oliver. (2007). Constraint and turnover in sex-biased gene expression in the genus Drosophila. Nature. 450(7167). 233–237. 239 indexed citations
18.
Fitzgerald, Peter, et al.. (2006). Comparative genomics of Drosophila and human core promoters. Genome biology. 7(7). R53–R53. 117 indexed citations
19.
Cerrato, Aniello, Michael Parisi, Fanis Missirlis, et al.. (2006). Genetic interactions between Drosophila melanogaster menin and Jun/Fos. Developmental Biology. 298(1). 59–70. 16 indexed citations
20.
Lü, Jining, et al.. (2004). Core Promoter Sequences Contribute to ovo-B Regulation in the Drosophila melanogaster Germline. Genetics. 169(1). 161–172. 19 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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