Jenna Wood

429 total citations
10 papers, 292 citations indexed

About

Jenna Wood is a scholar working on Molecular Biology, Genetics and Genetics. According to data from OpenAlex, Jenna Wood has authored 10 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Genetics and 3 papers in Genetics. Recurrent topics in Jenna Wood's work include Protein Kinase Regulation and GTPase Signaling (2 papers), Virus-based gene therapy research (2 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Jenna Wood is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (2 papers), Virus-based gene therapy research (2 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Jenna Wood collaborates with scholars based in United States and Germany. Jenna Wood's co-authors include V Stanojević, Joel F. Habener, Eva Tomás, David A. Williams, Anja Troeger, John C. Byrd, Amy J. Johnson, Leslie A. Andritsos, William Blum and Somesh Mohapatra and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Jenna Wood

10 papers receiving 290 citations

Peers

Jenna Wood

MB

EDM

SURGE

IMMUN

GENET

Monica Mancino Italy

Yinghong Yang China

Denise Sickert Switzerland

Xiaoli Xie China

Dorota Iwaszkiewicz‐Grześ Poland

Bowen Wu China

Manni Luthra‐Guptasarma India

Mouhannad Malek France

Yannick Waumans Belgium

Frederick Briccetti United States

Monica Mancino Italy

Jenna Wood

193 ×1.0

MB

58 ×0.9

EDM

36 ×0.6

SURGE

26 ×0.6

IMMUN

11 ×0.3

GENET

Citations per year, relative to Jenna Wood Jenna Wood (= 1×) peers Monica Mancino

Countries citing papers authored by Jenna Wood

Since Specialization

Citations

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

Fields of papers citing papers by Jenna Wood

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jenna Wood

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

All Works

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10 of 10 papers shown

1.

Gan, Li, Jenna Wood, Nelsa L. Estrella, et al.. (2022). A cell-penetrating peptide enhances delivery and efficacy of phosphorodiamidate morpholino oligomers in mdx mice. Molecular Therapy — Nucleic Acids. 30. 17–27. 33 indexed citations

2.

Schissel, Carly K., Somesh Mohapatra, Justin M. Wolfe, et al.. (2021). Deep learning to design nuclear-targeting abiotic miniproteins. Nature Chemistry. 13(10). 992–1000. 45 indexed citations

3.

López‐Vidal, Eva M., Carly K. Schissel, Somesh Mohapatra, et al.. (2021). Deep Learning Enables Discovery of a Short Nuclear Targeting Peptide for Efficient Delivery of Antisense Oligomers. SHILAP Revista de lepidopterología. 1(11). 2009–2020. 16 indexed citations

4.

Zhang, Jianbo, Jenna Wood, Huadong Sun, et al.. (2021). Pharmacokinetic/Pharmacodynamic Modeling of a Cell-Penetrating Peptide Phosphorodiamidate Morpholino Oligomer in mdx Mice. Pharmaceutical Research. 38(10). 1731–1745. 10 indexed citations

5.

Reddy, Pavankumar N.G., Maria Radu, Ke Xu, et al.. (2016). p21-activated kinase 2 regulates HSPC cytoskeleton, migration, and homing via CDC42 activation and interaction with β-Pix. Blood. 127(16). 1967–1975. 24 indexed citations

6.

Vita, Serena De, Rebekka K. Schneider, Michael Garcia, et al.. (2014). Loss of Function of TET2 Cooperates with Constitutively Active KIT in Murine and Human Models of Mastocytosis. PLoS ONE. 9(5). e96209–e96209. 29 indexed citations

7.

Troeger, Anja, Hee‐Don Chae, Mümine Şentürk, Jenna Wood, & David A. Williams. (2013). A Unique Carboxyl-terminal Insert Domain in the Hematopoietic-specific, GTPase-deficient Rho GTPase RhoH Regulates Post-translational Processing. Journal of Biological Chemistry. 288(51). 36451–36462. 9 indexed citations

8.

Troeger, Anja, Amy J. Johnson, Jenna Wood, et al.. (2012). RhoH is critical for cell-microenvironment interactions in chronic lymphocytic leukemia in mice and humans. Blood. 119(20). 4708–4718. 47 indexed citations

9.

Tomás, Eva, Jenna Wood, V Stanojević, & Joel F. Habener. (2011). GLP-1-derived nonapeptide GLP-1(28–36)amide inhibits weight gain and attenuates diabetes and hepatic steatosis in diet-induced obese mice. Regulatory Peptides. 169(1-3). 43–48. 40 indexed citations

10.

Tomás, Eva, Jenna Wood, V Stanojević, & Joel F. Habener. (2010). Glucagon‐like peptide‐1(9‐36)amide metabolite inhibits weight gain and attenuates diabetes and hepatic steatosis in diet‐induced obese mice. Diabetes Obesity and Metabolism. 13(1). 26–33. 39 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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