James T. Platt

2.3k total citations
28 papers, 1.8k citations indexed

About

James T. Platt is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, James T. Platt has authored 28 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 11 papers in Oncology and 7 papers in Cancer Research. Recurrent topics in James T. Platt's work include Cancer Genomics and Diagnostics (7 papers), Melanoma and MAPK Pathways (6 papers) and Protein Degradation and Inhibitors (4 papers). James T. Platt is often cited by papers focused on Cancer Genomics and Diagnostics (7 papers), Melanoma and MAPK Pathways (6 papers) and Protein Degradation and Inhibitors (4 papers). James T. Platt collaborates with scholars based in United States, United Kingdom and Switzerland. James T. Platt's co-authors include John M. Pawelek, Marcus Bosenberg, Stefano Sodi, Ashok K. Chakraborty, David Bermudes, David F. Stern, K. Brooks Low, William Damsky, David Dankort and Samuel I. Miller and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and Nature Biotechnology.

In The Last Decade

James T. Platt

28 papers receiving 1.8k citations

Peers

James T. Platt
Lawrence H. Cheung United States
Douglas M. Gersten United States
He Zhou China
Richard B. Halberg United States
Michael J. Feldhaus United States
Lawrence H. Cheung United States
James T. Platt
Citations per year, relative to James T. Platt James T. Platt (= 1×) peers Lawrence H. Cheung

Countries citing papers authored by James T. Platt

Since Specialization
Citations

This map shows the geographic impact of James T. Platt'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 T. Platt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James T. Platt more than expected).

Fields of papers citing papers by James T. Platt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James T. Platt

This figure shows the co-authorship network connecting the top 25 collaborators of James T. Platt. A scholar is included among the top collaborators of James T. Platt 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 T. Platt. James T. Platt 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.
Gershkovich, Peter, James T. Platt, Marios Konstantinos Tasoulis, et al.. (2018). TQuest, A Web-Based Platform to Enable Precision Medicine by Linking a Tumor’s Genetic Defects to Therapeutic Options. JCO Clinical Cancer Informatics. 2(2). 1–13. 1 indexed citations
2.
Langdon, Casey G., James T. Platt, Robert E. Means, et al.. (2017). Combinatorial Screening of Pancreatic Adenocarcinoma Reveals Sensitivity to Drug Combinations Including Bromodomain Inhibitor Plus Neddylation Inhibitor. Molecular Cancer Therapeutics. 16(6). 1041–1053. 12 indexed citations
3.
Gayvert, Kaitlyn, Omar M. Aly, James T. Platt, et al.. (2017). A Computational Approach for Identifying Synergistic Drug Combinations. PLoS Computational Biology. 13(1). e1005308–e1005308. 66 indexed citations
4.
Wali, Vikram B., Casey G. Langdon, Matthew A. Held, et al.. (2016). Systematic Drug Screening Identifies Tractable Targeted Combination Therapies in Triple-Negative Breast Cancer. Cancer Research. 77(2). 566–578. 38 indexed citations
5.
McFadden, David G., Katerina Politi, Arjun Bhutkar, et al.. (2016). Mutational landscape of EGFR- , MYC- , and Kras- driven genetically engineered mouse models of lung adenocarcinoma. Proceedings of the National Academy of Sciences. 113(42). E6409–E6417. 126 indexed citations
6.
Scortegagna, Marzia, Eric Lau, Tongwu Zhang, et al.. (2015). PDK1 and SGK3 Contribute to the Growth of BRAF-Mutant Melanomas and Are Potential Therapeutic Targets. Cancer Research. 75(7). 1399–1412. 44 indexed citations
7.
Damsky, William, Goran Micevic, Katrina Meeth, et al.. (2015). mTORC1 Activation Blocks BrafV600E-Induced Growth Arrest but Is Insufficient for Melanoma Formation. Cancer Cell. 27(1). 41–56. 87 indexed citations
8.
Langdon, Casey G., Matthew A. Held, James T. Platt, et al.. (2015). The broad‐spectrum receptor tyrosine kinase inhibitor dovitinib suppresses growth of BRAF ‐mutant melanoma cells in combination with other signaling pathway inhibitors. Pigment Cell & Melanoma Research. 28(4). 417–430. 13 indexed citations
9.
Park, Sin‐Aye, James T. Platt, Jong Woo Lee, et al.. (2015). E2F8 as a Novel Therapeutic Target for Lung Cancer. JNCI Journal of the National Cancer Institute. 107(9). 80 indexed citations
10.
Wali, Vikram B., Jonathan W. Haskins, Maureen Gilmore-Hebert, et al.. (2014). Convergent and Divergent Cellular Responses by ErbB4 Isoforms in Mammary Epithelial Cells. Molecular Cancer Research. 12(8). 1140–1155. 20 indexed citations
11.
Muthusamy, Viswanathan, et al.. (2013). The Hematopoietic Stem Cell Regulatory Gene Latexin Has Tumor-Suppressive Properties in Malignant Melanoma. Journal of Investigative Dermatology. 133(7). 1827–1833. 27 indexed citations
12.
Copeland, Holly E., Amy Pocewicz, David E. Naugle, et al.. (2013). Measuring the Effectiveness of Conservation: A Novel Framework to Quantify the Benefits of Sage-Grouse Conservation Policy and Easements in Wyoming. PLoS ONE. 8(6). e67261–e67261. 43 indexed citations
13.
Held, Matthew A., Casey G. Langdon, James T. Platt, et al.. (2012). Genotype-Selective Combination Therapies for Melanoma Identified by High-Throughput Drug Screening. Cancer Discovery. 3(1). 52–67. 96 indexed citations
14.
Damsky, William, David P. Curley, Manjula Santhanakrishnan, et al.. (2011). β-Catenin Signaling Controls Metastasis in Braf-Activated Pten-Deficient Melanomas. Cancer Cell. 20(6). 741–754. 267 indexed citations
15.
Pawelek, John M., Stefano Sodi, Ashok K. Chakraborty, et al.. (2002). Salmonella pathogenicity island-2 and anticancer activity in mice. Cancer Gene Therapy. 9(10). 813–818. 38 indexed citations
16.
Platt, James T., Stefano Sodi, Marianne Kelley, et al.. (2000). Antitumour effects of genetically engineered Salmonella in combination with radiation. European Journal of Cancer. 36(18). 2397–2402. 58 indexed citations
17.
Low, K. Brooks, Martina Ittensohn, Trung Bao Le, et al.. (1999). Lipid A mutant Salmonella with suppressed virulence and TNFα induction retain tumor-targeting in vivo. Nature Biotechnology. 17(1). 37–41. 407 indexed citations
18.
Sodi, Stefano, Ashok K. Chakraborty, James T. Platt, et al.. (1998). Melanoma × Macrophage Fusion Hybrids Acquire Increased Melanogenesis and Metastatic Potential: Altered N‐Glycosylation as an Underlying Mechanism. Pigment Cell Research. 11(5). 299–309. 22 indexed citations
19.
Sodi, Stefano, Ashok K. Chakraborty, Jean L. Bolognia, et al.. (1998). Melanoma × macrophage hybrids with enhanced metastatic potential. Clinical & Experimental Metastasis. 16(4). 299–312. 115 indexed citations
20.
Ak, Chakraborty, et al.. (1996). Polymerization of 5,6‐Dihydroxyindole‐2‐Carboxylic Acid to Melanin by the Pmel 17/Silver Locus Protein. European Journal of Biochemistry. 236(1). 180–188. 82 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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