Olivia Garijo

787 total citations
8 papers, 580 citations indexed

About

Olivia Garijo is a scholar working on Molecular Biology, Immunology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Olivia Garijo has authored 8 papers receiving a total of 580 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Immunology and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Olivia Garijo's work include Virus-based gene therapy research (2 papers), CRISPR and Genetic Engineering (2 papers) and Immune Response and Inflammation (2 papers). Olivia Garijo is often cited by papers focused on Virus-based gene therapy research (2 papers), CRISPR and Genetic Engineering (2 papers) and Immune Response and Inflammation (2 papers). Olivia Garijo collaborates with scholars based in United States, Japan and South Korea. Olivia Garijo's co-authors include Wendy L. Havran, Deborah A. Witherden, Petra Verdino, Ian A. Wilson, Luc Teyton, Stephanie Rieder, Wolfgang Fischer, Amanda S. MacLeod, Saskia Hemmers and Kerri Mowen and has published in prestigious journals such as Science, Journal of Clinical Investigation and Immunity.

In The Last Decade

Olivia Garijo

8 papers receiving 575 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Olivia Garijo United States	7	347	139	119	88	87	8	580
Lokesh A. Kalekar United States	8	455 1.3×	68 0.5×	38 0.3×	70 0.8×	110 1.3×	8	586
Qiang Cheng Australia	10	360 1.0×	161 1.2×	36 0.3×	43 0.5×	60 0.7×	10	584
Donggou He United States	6	508 1.5×	116 0.8×	139 1.2×	23 0.3×	216 2.5×	8	698
A. Cole Thies United States	9	114 0.3×	113 0.8×	119 1.0×	24 0.3×	56 0.6×	10	449
Véronique Adoue France	15	294 0.8×	377 2.7×	47 0.4×	161 1.8×	90 1.0×	21	809
Volker Blaschke Germany	14	365 1.1×	131 0.9×	136 1.1×	42 0.5×	91 1.0×	26	677
Paola Atzei Ireland	7	153 0.4×	118 0.8×	30 0.3×	16 0.2×	43 0.5×	9	316
Julia Maslovskaja Estonia	12	239 0.7×	209 1.5×	105 0.9×	65 0.7×	40 0.5×	14	554
Michiko Tojo Japan	14	74 0.2×	236 1.7×	113 0.9×	70 0.8×	48 0.6×	20	480
Victoria E. Kennedy United States	11	87 0.3×	143 1.0×	49 0.4×	35 0.4×	25 0.3×	21	315

Countries citing papers authored by Olivia Garijo

Since Specialization

Citations

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

Fields of papers citing papers by Olivia Garijo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olivia Garijo

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

All Works

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8 of 8 papers shown

1.

Witherden, Deborah A., Olivia Garijo, Ryan Kelly, H. Kiyomi Komori, & Wendy L. Havran. (2019). TCR-ligand interactions are required for murine epidermal Vγ3Vδ1 T cell development. The Journal of Immunology. 202(1_Supplement). 53.4–53.4. 2 indexed citations

2.

Simpson, Elizabeth M., et al.. (2018). CD46 Null Packaging Cell Line Improves Measles Lentiviral Vector Production and Gene Delivery to Hematopoietic Stem and Progenitor Cells. Molecular Therapy — Methods & Clinical Development. 13. 27–39. 11 indexed citations

3.

Heffner, Garrett C., Melissa Bonner, Francis J. Pierciey, et al.. (2017). Prostaglandin E2 Increases Lentiviral Vector Transduction Efficiency of Adult Human Hematopoietic Stem and Progenitor Cells. Molecular Therapy. 26(1). 320–328. 62 indexed citations

4.

MacLeod, Amanda S., Ross Rudolph, Ross Corriden, et al.. (2014). Skin-Resident T Cells Sense Ultraviolet Radiation–Induced Injury and Contribute to DNA Repair. The Journal of Immunology. 192(12). 5695–5702. 56 indexed citations

5.

Meehan, Terrence F., Deborah A. Witherden, Chang‐Hoon Kim, et al.. (2013). Protection against colitis by CD100-dependent modulation of intraepithelial γδ T lymphocyte function. Mucosal Immunology. 7(1). 134–142. 38 indexed citations

6.

MacLeod, Amanda S., Saskia Hemmers, Olivia Garijo, et al.. (2013). Dendritic epidermal T cells regulate skin antimicrobial barrier function. Journal of Clinical Investigation. 123(10). 4364–4374. 118 indexed citations

7.

Witherden, Deborah A., Megumi Watanabe, Olivia Garijo, et al.. (2012). The CD100 Receptor Interacts with Its Plexin B2 Ligand to Regulate Epidermal γδ T Cell Function. Immunity. 37(2). 314–325. 127 indexed citations

8.

Witherden, Deborah A., Petra Verdino, Stephanie Rieder, et al.. (2010). The Junctional Adhesion Molecule JAML Is a Costimulatory Receptor for Epithelial γδ T Cell Activation. Science. 329(5996). 1205–1210. 166 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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