Chad Torrice

5.8k total citations · 2 hit papers
35 papers, 3.6k citations indexed

About

Chad Torrice is a scholar working on Molecular Biology, Physiology and Organic Chemistry. According to data from OpenAlex, Chad Torrice has authored 35 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Physiology and 6 papers in Organic Chemistry. Recurrent topics in Chad Torrice's work include Telomeres, Telomerase, and Senescence (7 papers), Cancer-related Molecular Pathways (4 papers) and HIV-related health complications and treatments (4 papers). Chad Torrice is often cited by papers focused on Telomeres, Telomerase, and Senescence (7 papers), Cancer-related Molecular Pathways (4 papers) and HIV-related health complications and treatments (4 papers). Chad Torrice collaborates with scholars based in United States, Finland and Germany. Chad Torrice's co-authors include Norman E. Sharpless, Janakiraman Krishnamurthy, Matthew R. Ramsey, Lishan Su, Khalid Al-Regaiey, Kovalev Gi, Keith L. Ligon, Angela Koh, Susan Bonner‐Weir and Hanna K. Sanoff and has published in prestigious journals such as Nature, Journal of Clinical Investigation and Gastroenterology.

In The Last Decade

Chad Torrice

33 papers receiving 3.6k citations

Hit Papers

Ink4a/Arf expression is a biomarker of aging 2004 2026 2011 2018 2004 2006 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chad Torrice United States 19 1.8k 1.4k 635 527 418 35 3.6k
Saghi Ghaffari United States 36 2.6k 1.5× 835 0.6× 689 1.1× 647 1.2× 620 1.5× 80 4.6k
Janakiraman Krishnamurthy United States 19 3.0k 1.7× 2.6k 1.9× 928 1.5× 1000 1.9× 610 1.5× 25 5.7k
Eric Campeau United States 17 2.2k 1.2× 1.2k 0.8× 558 0.9× 705 1.3× 438 1.0× 32 3.6k
Rémi-Martin Laberge United States 16 1.9k 1.1× 1.7k 1.2× 395 0.6× 851 1.6× 708 1.7× 21 3.9k
George A. Garinis Greece 32 2.6k 1.5× 720 0.5× 486 0.8× 501 1.0× 539 1.3× 63 3.8k
Laura C. Greaves United Kingdom 32 2.3k 1.3× 637 0.5× 373 0.6× 201 0.4× 448 1.1× 54 3.5k
Ergün Sahin United States 18 2.4k 1.4× 1.3k 0.9× 509 0.8× 338 0.6× 651 1.6× 27 4.2k
Karthik B. Jeganathan United States 26 3.9k 2.2× 1.8k 1.3× 936 1.5× 693 1.3× 630 1.5× 39 6.0k
Christopher D. Wiley United States 21 1.7k 1.0× 1.7k 1.2× 217 0.3× 691 1.3× 386 0.9× 34 3.6k
Albert R. Davalos United States 20 2.3k 1.3× 2.0k 1.5× 636 1.0× 1.0k 1.9× 623 1.5× 27 4.3k

Countries citing papers authored by Chad Torrice

Since Specialization
Citations

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

Fields of papers citing papers by Chad Torrice

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chad Torrice

This figure shows the co-authorship network connecting the top 25 collaborators of Chad Torrice. A scholar is included among the top collaborators of Chad Torrice 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 Chad Torrice. Chad Torrice 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
2.
Anderson, Brian, John D. Norris, Chad Torrice, et al.. (2023). Structural Determinants of the Binding and Activation of Estrogen Receptor α by Phenolic Thieno[2,3‐ d ]pyrimidines. Helvetica Chimica Acta. 106(9). 2 indexed citations
3.
Norris, John D., Sandeep Artham, Chad Torrice, et al.. (2022). A New Chemotype of Chemically Tractable Nonsteroidal Estrogens Based on a Thieno[2,3- d ]pyrimidine Core. ACS Medicinal Chemistry Letters. 13(7). 1151–1158. 2 indexed citations
5.
Koyioni, Maria, Chad Torrice, William A. Murphy, et al.. (2021). Design and evaluation of 1,2,3-dithiazoles and fused 1,2,4-dithiazines as anti-cancer agents. Bioorganic & Medicinal Chemistry Letters. 43. 128078–128078. 7 indexed citations
6.
Torrice, Chad, Christin E. Burd, Yan Liu, et al.. (2020). Expression of p16 INK4a in peripheral blood T-cells is a biomarker of human aging. UNC Libraries. 18 indexed citations
7.
Derebail, Vimal K., Karlyn A. Martin, Russell P. Grant, et al.. (2020). Clinical Pharmacology of Apixaban in Nephrotic Syndrome. Journal of the American Society of Nephrology. 31(10S). 722–722. 1 indexed citations
8.
Asquith, Christopher R. M., et al.. (2019). Anti-tubercular activity of novel 4-anilinoquinolines and 4-anilinoquinazolines. Bioorganic & Medicinal Chemistry Letters. 29(18). 2695–2699. 19 indexed citations
9.
Asquith, Christopher R. M., Benedict‐Tilman Berger, James M. Bennett, et al.. (2019). SGC-GAK-1: A Chemical Probe for Cyclin G Associated Kinase (GAK). Journal of Medicinal Chemistry. 62(5). 2830–2836. 45 indexed citations
10.
Wood, William A., Janakiraman Krishnamurthy, Natalia Mitin, et al.. (2016). Chemotherapy and Stem Cell Transplantation Increase p16 INK4a Expression, a Biomarker of T-cell Aging. EBioMedicine. 11. 227–238. 56 indexed citations
12.
Pustavoitau, Aliaksei, Viachaslau Barodka, Norman E. Sharpless, et al.. (2015). Role of senescence marker p16INK4a measured in peripheral blood T-lymphocytes in predicting length of hospital stay after coronary artery bypass surgery in older adults. Experimental Gerontology. 74. 29–36. 29 indexed citations
13.
Johnson, Søren M., Chad Torrice, Kimberly B. Monahan, et al.. (2010). Mitigation of hematologic radiation toxicity in mice through pharmacological quiescence induced by CDK4/6 inhibition. Journal of Clinical Investigation. 120(7). 2528–2536. 134 indexed citations
14.
Rozenberg, Gabriela I., Kimberly B. Monahan, Chad Torrice, James E. Bear, & Norman E. Sharpless. (2010). Metastasis in an orthotopic murine model of melanoma is independent of RAS/RAF mutation. Melanoma Research. 20(5). 361–371. 28 indexed citations
15.
Liu, Yan, Hanna K. Sanoff, Hyunsoon Cho, et al.. (2009). Expression of p16INK4a in peripheral blood T‐cells is a biomarker of human aging. Aging Cell. 8(4). 439–448. 357 indexed citations
16.
Shields, Janiel M., Nancy E. Thomas, Melissa A. Cregger, et al.. (2007). Lack of Extracellular Signal-Regulated Kinase Mitogen-Activated Protein Kinase Signaling Shows a New Type of Melanoma. Cancer Research. 67(4). 1502–1512. 66 indexed citations
17.
Ramsey, Matthew R., Janakiraman Krishnamurthy, Xin‐Hai Pei, et al.. (2007). Expression of p16Ink4a Compensates for p18Ink4c Loss in Cyclin-Dependent Kinase 4/6–Dependent Tumors and Tissues. Cancer Research. 67(10). 4732–4741. 53 indexed citations
18.
Keku, Temitope O., Chad Torrice, Xiaping He, et al.. (2007). RNA expression analysis of formalin-fixed paraffin-embedded tumors. Laboratory Investigation. 87(4). 383–391. 132 indexed citations
19.
Krishnamurthy, Janakiraman, Chad Torrice, Matthew R. Ramsey, et al.. (2004). Ink4a/Arf expression is a biomarker of aging. Journal of Clinical Investigation. 114(9). 1299–1307. 1167 indexed citations breakdown →
20.
Krishnamurthy, Janakiraman, Chad Torrice, Matthew R. Ramsey, et al.. (2004). Ink4a/Arf expression is a biomarker of aging. Journal of Clinical Investigation. 114(9). 1299–1307. 105 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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