Tina Garyantes

1.8k total citations · 1 hit paper
16 papers, 1.3k citations indexed

About

Tina Garyantes is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Tina Garyantes has authored 16 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Immunology and 4 papers in Genetics. Recurrent topics in Tina Garyantes's work include Estrogen and related hormone effects (4 papers), Immunotherapy and Immune Responses (4 papers) and Computational Drug Discovery Methods (2 papers). Tina Garyantes is often cited by papers focused on Estrogen and related hormone effects (4 papers), Immunotherapy and Immune Responses (4 papers) and Computational Drug Discovery Methods (2 papers). Tina Garyantes collaborates with scholars based in United States, Switzerland and France. Tina Garyantes's co-authors include Robert Hertzberg, William P. Janzen, David Burns, Darren V. S. Green, Dragan A. Cirovic, Jeff W. Paslay, Ulrich Schopfer, Ricardo Macarrón, G. Sitta Sittampalam and Martyn Banks and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Nature Reviews Drug Discovery.

In The Last Decade

Tina Garyantes

14 papers receiving 1.2k citations

Hit Papers

Impact of high-throughput... 2011 2026 2016 2021 2011 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Impact of high-throughput screening in biomedical research
    2011 920 citations Ricardo Macarrón, Martyn Banks et al. Nature Reviews Drug Discovery profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tina Garyantes United States 10 734 390 155 145 121 16 1.3k
Jeff W. Paslay United States 5 550 0.7× 356 0.9× 144 0.9× 145 1.0× 116 1.0× 6 971
Dragan A. Cirovic United Kingdom 6 547 0.7× 357 0.9× 171 1.1× 144 1.0× 117 1.0× 8 1.0k
Christian N. Parker Switzerland 21 955 1.3× 292 0.7× 77 0.5× 111 0.8× 79 0.7× 47 1.4k
Florian Nigsch Switzerland 21 725 1.0× 582 1.5× 76 0.5× 152 1.0× 220 1.8× 36 1.4k
William D. Pennie United States 17 893 1.2× 440 1.1× 132 0.9× 116 0.8× 80 0.7× 23 1.8k
Martyn Banks United States 17 1.0k 1.4× 431 1.1× 254 1.6× 241 1.7× 128 1.1× 37 1.7k
Nicola Tolliday United States 20 1.6k 2.2× 223 0.6× 134 0.9× 144 1.0× 190 1.6× 28 2.1k
Alex. M. Weir United Kingdom 2 424 0.6× 371 1.0× 121 0.8× 92 0.6× 74 0.6× 2 956
Owen B. Wallace United States 16 689 0.9× 405 1.0× 146 0.9× 403 2.8× 91 0.8× 27 1.6k
Ricardo Macarrón United States 17 1.3k 1.7× 582 1.5× 373 2.4× 285 2.0× 161 1.3× 26 2.0k

Countries citing papers authored by Tina Garyantes

Since Specialization
Citations

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

Fields of papers citing papers by Tina Garyantes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tina Garyantes

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

All Works

16 of 16 papers shown
1.
Natale, Christopher A., Israel Olayide, Christopher K. Arnatt, et al.. (2025). LNS8801: An Enantiomerically Pure Agonist of the G Protein–Coupled Estrogen Receptor Suitable for Clinical Development. Cancer Research Communications. 5(4). 556–568.
2.
Rodon, Jordi, Marya Chaney, Justine V. Cohen, et al.. (2023). 627 The effect of LNS8801 in combination with pembrolizumab in patients with treatment-refractory cutaneous melanoma. SHILAP Revista de lepidopterología. A716–A716.
3.
Ambrosini, Grazia, Christopher A. Natale, Elgilda Musi, Tina Garyantes, & Gary K. Schwartz. (2023). The GPER Agonist LNS8801 Induces Mitotic Arrest and Apoptosis in Uveal Melanoma Cells. Cancer Research Communications. 3(4). 540–547. 10 indexed citations
4.
Shoushtari, Alexander N., Marya Chaney, Justine V. Cohen, et al.. (2023). The effect of LNS8801 alone and in combination with pembrolizumab in patients with metastatic uveal melanoma.. Journal of Clinical Oncology. 41(16_suppl). 9543–9543. 6 indexed citations
5.
Rodón, Jordi, Marya Chaney, Justine V. Cohen, et al.. (2022). 759 Phase 1b study of LNS8801 in combination with pembrolizumab in patients with secondary resistance to immune checkpoint inhibitors. Regular and Young Investigator Award Abstracts. A791–A791. 1 indexed citations
6.
7.
Muller, Carolyn Y., Ursa Brown‐Glaberman, Marya Chaney, et al.. (2021). Phase 1 trial of a novel, first-in-class G protein-coupled estrogen receptor (GPER) agonist, LNS8801, in patients with advanced or recurrent treatment-refractory solid malignancies.. Journal of Clinical Oncology. 39(15_suppl). 3084–3084. 10 indexed citations
8.
Garyantes, Tina, et al.. (2021). Abstract 1282: IND-enabling characterization of the selective GPER agonist, LNS8801. Cancer Research. 81(13_Supplement). 1282–1282. 3 indexed citations
9.
Wang-Fischer, Yanlin & Tina Garyantes. (2018). Improving the Reliability and Utility of Streptozotocin-Induced Rat Diabetic Model. Journal of Diabetes Research. 2018. 1–14. 126 indexed citations
10.
Buchser, William, Mark A. Collins, Tina Garyantes, et al.. (2014). Assay Development Guidelines for Image-Based High Content Screening, High Content Analysis and High Content Imaging. 53 indexed citations
11.
Macarrón, Ricardo, Martyn Banks, Dejan Bojanic, et al.. (2011). Impact of high-throughput screening in biomedical research. Nature Reviews Drug Discovery. 10(3). 188–195. 920 indexed citations breakdown →
12.
Li, Zhuyin, et al.. (2009). A robust assay measuring GLUT4 translocation in rat myoblasts overexpressing GLUT4-myc and AS160_v2. Analytical Biochemistry. 397(2). 233–240. 9 indexed citations
13.
Li, Zhuyin, et al.. (2003). Identification of Gap Junction Blockers Using Automated Fluorescence Microscopy Imaging. SLAS DISCOVERY. 8(5). 489–499. 45 indexed citations
14.
Fogel, Paul, et al.. (2002). The Confirmation Rate of Primary Hits: A Predictive Model. SLAS DISCOVERY. 7(3). 175–190. 14 indexed citations
15.
Tang, Weimin, Jiesheng Kang, David Rampe, et al.. (2001). Development and Evaluation of High Throughput Functional Assay Methods for hERG Potassium Channel. SLAS DISCOVERY. 6(5). 325–331. 59 indexed citations
16.
Tang, Weimin, Jiesheng Kang, David Rampe, et al.. (2001). Development and Evaluation of High Throughput Functional Assay Methods for hERG Potassium Channel. 6(5). 325–331. 11 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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