Olivia Hibbitt

576 total citations
17 papers, 462 citations indexed

About

Olivia Hibbitt is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Olivia Hibbitt has authored 17 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 10 papers in Genetics and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Olivia Hibbitt's work include Virus-based gene therapy research (6 papers), CRISPR and Genetic Engineering (5 papers) and Animal Genetics and Reproduction (4 papers). Olivia Hibbitt is often cited by papers focused on Virus-based gene therapy research (6 papers), CRISPR and Genetic Engineering (5 papers) and Animal Genetics and Reproduction (4 papers). Olivia Hibbitt collaborates with scholars based in United Kingdom, Japan and Australia. Olivia Hibbitt's co-authors include John Parrington, Kevin Coward, Niall Bromage, Richard Wade‐Martins, Keith M. Channon, Keith T. Jones, Chris P. Ponting, Peter Savolainen, Christina A. Bursill and Hiroki Kubota and has published in prestigious journals such as PLoS ONE, Biochemical and Biophysical Research Communications and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Olivia Hibbitt

17 papers receiving 443 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Olivia Hibbitt United Kingdom 12 164 151 150 134 123 17 462
T. Hirai Japan 10 124 0.8× 181 1.2× 113 0.8× 195 1.5× 114 0.9× 23 421
Zuxu Yao Canada 9 248 1.5× 150 1.0× 255 1.7× 203 1.5× 318 2.6× 9 590
Annamaria Liguoro Italy 12 180 1.1× 79 0.5× 76 0.5× 107 0.8× 20 0.2× 21 405
Ya-Wen Chang Taiwan 12 88 0.5× 203 1.3× 124 0.8× 201 1.5× 58 0.5× 17 433
Baofeng Huang China 12 221 1.3× 449 3.0× 119 0.8× 310 2.3× 40 0.3× 15 683
Ryo Horiguchi Japan 17 299 1.8× 530 3.5× 191 1.3× 453 3.4× 90 0.7× 36 859
Joanna Queen United States 6 134 0.8× 296 2.0× 122 0.8× 76 0.6× 37 0.3× 9 360
Xinping Zhu China 12 229 1.4× 174 1.2× 24 0.2× 62 0.5× 31 0.3× 45 493
Yoshinaga Takayama Japan 15 260 1.6× 123 0.8× 37 0.2× 115 0.9× 28 0.2× 24 704
Anirudh Natarajan United States 7 477 2.9× 356 2.4× 136 0.9× 31 0.2× 75 0.6× 10 642

Countries citing papers authored by Olivia Hibbitt

Since Specialization
Citations

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

Fields of papers citing papers by Olivia Hibbitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olivia Hibbitt

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

All Works

17 of 17 papers shown
1.
Trent, Ronald J., Cliff Meldrum, Peter Kennedy, et al.. (2023). Making good on the promise of genomics in healthcare: the NSW Health perspective. Australian Health Review. 47(6). 631–633. 1 indexed citations
2.
Kerr, Alastair G., Lawrence C. S. Tam, Ashley Hale, et al.. (2017). A Genomic DNA Reporter Screen Identifies Squalene Synthase Inhibitors That Act Cooperatively with Statins to Upregulate the Low-Density Lipoprotein Receptor. Journal of Pharmacology and Experimental Therapeutics. 361(3). 417–428. 3 indexed citations
3.
Sacilotto, Natalia, Josefa Castillo, Ángela L. Riffo‐Campos, et al.. (2015). Growth Arrest Specific 1 (Gas1) Gene Overexpression in Liver Reduces the In Vivo Progression of Murine Hepatocellular Carcinoma and Partially Restores Gene Expression Levels. PLoS ONE. 10(7). e0132477–e0132477. 15 indexed citations
4.
Hibbitt, Olivia & Richard Wade‐Martins. (2011). High Capacity Extrachromosomal Gene Expression Vectors. Methods in molecular biology. 738. 19–40. 2 indexed citations
5.
Hibbitt, Olivia, C. Owen, Milena Cioroch, et al.. (2011). RNAi-mediated knockdown of HMG CoA reductase enhances gene expression from physiologically regulated low-density lipoprotein receptor therapeutic vectors in vivo. Gene Therapy. 19(4). 463–467. 17 indexed citations
6.
Hibbitt, Olivia, et al.. (2010). Targeted Gene Knockdown of HMG CoA Reductase Increases Transgene Expression from Genomic DNA LDLR Mini-Gene Vectors In Vitro and In Vivo: Increased Transgene Expression from Genomic LDLR Mini-Gene Vectors In Vitro and In Vivo Following Targeted Knockdown of HMG CoA Reductase. Human Gene Therapy. 21(4). 505–505. 3 indexed citations
7.
Hibbitt, Olivia, et al.. (2009). Long-term Physiologically Regulated Expression of the Low-density Lipoprotein Receptor In Vivo Using Genomic DNA Mini-gene Constructs. Molecular Therapy. 18(2). 317–326. 21 indexed citations
8.
Bursill, Christina A., Eileen McNeill, L Wang, et al.. (2008). Lentiviral gene transfer to reduce atherosclerosis progression by long-term CC-chemokine inhibition. Gene Therapy. 16(1). 93–102. 27 indexed citations
9.
Hibbitt, Olivia, Richard P. Harbottle, Simon N. Waddington, et al.. (2007). Delivery and long‐term expression of a 135 kb LDLR genomic DNA locus in vivo by hydrodynamic tail vein injection. The Journal of Gene Medicine. 9(6). 488–497. 35 indexed citations
10.
Parrington, John, Kevin Coward, Olivia Hibbitt, et al.. (2007). In vivo gene transfer into the testis by electroporation and viral infection--a novel way to study testis and sperm function.. PubMed. 65. 469–74. 7 indexed citations
11.
Hibbitt, Olivia & Richard Wade‐Martins. (2006). Delivery of Large Genomic DNA Inserts > 100 kb Using HSV-1 Amplicons. Current Gene Therapy. 6(3). 325–336. 25 indexed citations
12.
13.
14.
Coward, Kevin, Chris P. Ponting, Olivia Hibbitt, et al.. (2005). Phospholipase Cζ, the trigger of egg activation in mammals, is present in a non-mammalian species. Reproduction. 130(2). 157–163. 76 indexed citations
15.
Coward, Kevin, Albert J. Poustka, Olivia Hibbitt, et al.. (2003). Cloning of a novel phospholipase C-δ isoform from pacific purple sea urchin (Strongylocentrotus purpuratus) gametes and its expression during early embryonic development. Biochemical and Biophysical Research Communications. 313(4). 894–901. 14 indexed citations
16.
Coward, Kevin, Mark G. Larman, Olivia Hibbitt, et al.. (2003). Teleost fish spermatozoa contain a cytosolic protein factor that induces calcium release in sea urchin egg homogenates and triggers calcium oscillations when injected into mouse oocytes. Biochemical and Biophysical Research Communications. 305(2). 299–304. 36 indexed citations
17.
Coward, Kevin, Niall Bromage, Olivia Hibbitt, & John Parrington. (2002). Gamete physiology, fertilization and egg activation in teleost fish. Reviews in Fish Biology and Fisheries. 12(1). 33–58. 147 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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