James Watters

2.9k total citations
40 papers, 1.9k citations indexed

About

James Watters is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, James Watters has authored 40 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 14 papers in Oncology and 13 papers in Cancer Research. Recurrent topics in James Watters's work include Cancer Genomics and Diagnostics (9 papers), Pharmacogenetics and Drug Metabolism (8 papers) and PI3K/AKT/mTOR signaling in cancer (6 papers). James Watters is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Pharmacogenetics and Drug Metabolism (8 papers) and PI3K/AKT/mTOR signaling in cancer (6 papers). James Watters collaborates with scholars based in United States, France and Netherlands. James Watters's co-authors include Howard L. McLeod, William F. Dietrich, Tim Demuth, Andrey Loboda, Pearl S. Huang, Hongyue Dai, Michael Nebozhyn, Aldi T. Kraja, Michael A. Province and N.V. Rajeshkumar and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

James Watters

40 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Watters United States 21 1.2k 815 400 326 237 40 1.9k
J I Johnson United States 7 1.3k 1.0× 853 1.0× 316 0.8× 154 0.5× 148 0.6× 7 2.0k
Olga Timofeeva United States 19 1.1k 0.8× 606 0.7× 246 0.6× 312 1.0× 162 0.7× 49 1.9k
George Vande Woude United States 17 1.5k 1.2× 705 0.9× 311 0.8× 556 1.7× 279 1.2× 30 2.7k
Kyong‐Ah Yoon South Korea 23 910 0.7× 526 0.6× 593 1.5× 368 1.1× 157 0.7× 76 1.6k
Melissa J. LaBonte United States 27 1.2k 1.0× 1.3k 1.6× 526 1.3× 393 1.2× 185 0.8× 78 2.6k
Deepali Sachdev United States 25 1.6k 1.3× 707 0.9× 563 1.4× 195 0.6× 246 1.0× 33 2.2k
Carlos Becerra United States 24 1.4k 1.1× 1.1k 1.3× 379 0.9× 398 1.2× 141 0.6× 98 2.5k
Diane L. Persons United States 29 1.4k 1.1× 1.3k 1.6× 608 1.5× 409 1.3× 331 1.4× 64 3.1k
I Taylor United States 19 1.6k 1.3× 553 0.7× 395 1.0× 335 1.0× 190 0.8× 40 2.9k
Ken Brown United Kingdom 12 1.5k 1.3× 862 1.1× 493 1.2× 105 0.3× 220 0.9× 16 2.2k

Countries citing papers authored by James Watters

Since Specialization
Citations

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

Fields of papers citing papers by James Watters

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Watters

This figure shows the co-authorship network connecting the top 25 collaborators of James Watters. A scholar is included among the top collaborators of James Watters 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 James Watters. James Watters 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
1.
Casaletto, Jessica B., Dejan Maglic, B. Barry Touré, et al.. (2021). Abstract 1455: RLY-4008, a novel precision therapy for FGFR2-driven cancers designed to potently and selectively inhibit FGFR2 and FGFR2 resistance mutations. Cancer Research. 81(13_Supplement). 1455–1455. 13 indexed citations
2.
Hata, Aaron N., Hannah L. Archibald, María Gomez‐Caraballo, et al.. (2017). Synergistic activity and heterogeneous acquired resistance of combined MDM2 and MEK inhibition in KRAS mutant cancers. Oncogene. 36(47). 6581–6591. 28 indexed citations
3.
Jung, Joonil, Joon Sang Lee, Mark A. Dickson, et al.. (2016). TP53 mutations emerge with HDM2 inhibitor SAR405838 treatment in de-differentiated liposarcoma. Nature Communications. 7(1). 12609–12609. 78 indexed citations
4.
Nunes, Manoel, Patricia Vrignaud, Sophie Vacher, et al.. (2015). Evaluating Patient-Derived Colorectal Cancer Xenografts as Preclinical Models by Comparison with Patient Clinical Data. Cancer Research. 75(8). 1560–1566. 56 indexed citations
5.
Krop, Ian E., Tim Demuth, Tina Guthrie, et al.. (2012). Phase I Pharmacologic and Pharmacodynamic Study of the Gamma Secretase (Notch) Inhibitor MK-0752 in Adult Patients With Advanced Solid Tumors. Journal of Clinical Oncology. 30(19). 2307–2313. 251 indexed citations
6.
Nebozhyn, Michael, James Watters, Peter Shaw, et al.. (2011). EMT is the dominant program in human colon cancer. BMC Medical Genomics. 4(1). 9–9. 233 indexed citations
7.
Loboda, Andrey, Michael Nebozhyn, Jason P. Frazier, et al.. (2010). A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors. BMC Medical Genomics. 3(1). 26–26. 107 indexed citations
8.
Watters, James, Chun Cheng, Pradip K. Majumder, et al.. (2009). De novo Discovery of a γ-Secretase Inhibitor Response Signature Using a Novel In vivo Breast Tumor Model. Cancer Research. 69(23). 8949–8957. 31 indexed citations
9.
Malkov, Vladislav A., Kyle Serikawa, James Watters, et al.. (2009). Multiplexed measurements of gene signatures in different analytes using the Nanostring nCounter™ Assay System. BMC Research Notes. 2(1). 80–80. 120 indexed citations
10.
Watters, James, Chun Cheng, Maureen Pickarski, et al.. (2007). Inverse relationship between matrix remodeling and lipid metabolism during osteoarthritis progression in the STR/ORT mouse. Arthritis & Rheumatism. 56(9). 2999–3009. 30 indexed citations
11.
Hou, Weiying, James Watters, & Howard L. McLeod. (2004). Simple and rapid docetaxel assay in plasma by protein precipitation and high-performance liquid chromatography–tandem mass spectrometry. Journal of Chromatography B. 804(2). 263–267. 42 indexed citations
12.
Watters, James, et al.. (2004). Analysis of variation in mouse TPMT genotype, expression and activity. Pharmacogenetics. 14(4). 247–254. 7 indexed citations
13.
Thomas, Fabienne, Howard L. McLeod, & James Watters. (2004). Pharmacogenomics: The Influence of Genomic Variation on Drug Response. Current Topics in Medicinal Chemistry. 4(13). 1397–1407. 22 indexed citations
14.
Watters, James, et al.. (2003). A mouse-based strategy for cyclophosphamide pharmacogenomic discovery. Journal of Applied Physiology. 95(4). 1352–1360. 27 indexed citations
15.
Watters, James & Howard L. McLeod. (2003). Using genome-wide mapping in the mouse to identify genes that influence drug response. Trends in Pharmacological Sciences. 24(2). 55–58. 15 indexed citations
16.
Watters, James & Howard L. McLeod. (2003). Cancer pharmacogenomics: current and future applications. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1603(2). 99–111. 105 indexed citations
17.
McLeod, Howard L., et al.. (2003). Using genetic variation to optimize cancer chemotherapy.. PubMed. 1(2). 107–11. 7 indexed citations
18.
Watters, James, Ken Dewar, Jessica A. Lehoczky, Victor Boyartchuk, & William F. Dietrich. (2001). Kif1C, a kinesin-like motor protein, mediates mouse macrophage resistance to anthrax lethal factor. Current Biology. 11(19). 1503–1511. 65 indexed citations
19.
Watters, James & William F. Dietrich. (2001). Genetic, Physical, and Transcript Map of the Ltxs1 Region of Mouse Chromosome 11. Genomics. 73(2). 223–231. 23 indexed citations
20.

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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