Ji Luo

21.9k total citations · 10 hit papers
99 papers, 16.0k citations indexed

About

Ji Luo is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Ji Luo has authored 99 papers receiving a total of 16.0k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Molecular Biology, 24 papers in Oncology and 15 papers in Cell Biology. Recurrent topics in Ji Luo's work include Cancer-related Molecular Pathways (17 papers), PI3K/AKT/mTOR signaling in cancer (15 papers) and Protein Kinase Regulation and GTPase Signaling (13 papers). Ji Luo is often cited by papers focused on Cancer-related Molecular Pathways (17 papers), PI3K/AKT/mTOR signaling in cancer (15 papers) and Protein Kinase Regulation and GTPase Signaling (13 papers). Ji Luo collaborates with scholars based in United States, China and Japan. Ji Luo's co-authors include Lewis C. Cantley, Jeffrey A. Engelman, Stephen J. Elledge, Nicole L. Solimini, Brendan D. Manning, Channing J. Der, Adrienne D. Cox, Alec C. Kimmelman, Stephen W. Fesik and Agata Smogorzewska and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Ji Luo

93 papers receiving 15.8k citations

Hit Papers

The evolution of phosphatidylinositol 3-kinases as regula... 2003 2026 2010 2018 2006 2007 2014 2009 2003 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ji Luo United States 43 12.1k 4.2k 2.7k 1.7k 1.5k 99 16.0k
Yiling Lu United States 64 11.6k 1.0× 3.5k 0.8× 2.9k 1.1× 1.8k 1.1× 1.4k 0.9× 209 15.6k
Jane B. Trepel United States 74 11.8k 1.0× 4.4k 1.1× 3.2k 1.2× 1.4k 0.8× 2.2k 1.5× 290 17.6k
Akira Nakagawara Japan 69 11.4k 0.9× 5.3k 1.3× 4.4k 1.6× 1.6k 0.9× 1.4k 0.9× 347 18.0k
Nicholas Mitsiades United States 66 10.1k 0.8× 4.5k 1.1× 2.4k 0.9× 824 0.5× 1.9k 1.3× 172 15.3k
Daniel S. Peeper Netherlands 47 8.9k 0.7× 4.6k 1.1× 2.6k 1.0× 1.3k 0.7× 2.4k 1.6× 115 14.1k
Linda Z. Penn Canada 61 10.3k 0.9× 4.0k 0.9× 4.7k 1.7× 1.2k 0.7× 1.3k 0.8× 139 14.7k
Martin McMahon United States 72 12.9k 1.1× 7.2k 1.7× 2.6k 0.9× 1.9k 1.1× 2.7k 1.8× 167 17.9k
Emily H. Cheng United States 48 12.6k 1.0× 2.6k 0.6× 2.5k 0.9× 1.8k 1.0× 2.1k 1.4× 94 16.4k
Joyce M. Slingerland United States 60 10.3k 0.9× 8.1k 1.9× 3.0k 1.1× 1.9k 1.1× 1.0k 0.7× 120 15.5k
Alex Toker United States 73 15.1k 1.2× 3.1k 0.7× 2.6k 0.9× 3.7k 2.2× 2.3k 1.5× 136 20.5k

Countries citing papers authored by Ji Luo

Since Specialization
Citations

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

Fields of papers citing papers by Ji Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ji Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Ji Luo. A scholar is included among the top collaborators of Ji Luo 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 Ji Luo. Ji Luo 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.
Song, Yang, et al.. (2025). Quantitative Targeted Analysis of Antibody Fc Glycosylation by Glyco-MRM. Journal of Proteome Research. 24(11). 5793–5802.
3.
Cataisson, Christophe, Howard H. Yang, Wei‐Chun Lee, et al.. (2024). Protein phosphatase 6 activates NF-κB to confer sensitivity to MAPK pathway inhibitors in KRAS - and BRAF -mutant cancer cells. Science Signaling. 17(836). eadd5073–eadd5073.
4.
So, Jae Young, Abdul Ahad, Noémi Kedei, et al.. (2024). Loss of tumor suppressors promotes inflammatory tumor microenvironment and enhances LAG3+T cell mediated immune suppression. Nature Communications. 15(1). 5873–5873. 8 indexed citations
5.
Lee, Chih-Shia, et al.. (2023). A Nonconserved Histidine Residue on KRAS Drives Paralog Selectivity of the KRASG12D Inhibitor MRTX1133. Cancer Research. 83(17). 2816–2823. 11 indexed citations
6.
Sanchez, Vanesa C., Howard H. Yang, Justin Lack, et al.. (2022). Host CLIC4 expression in the tumor microenvironment is essential for breast cancer metastatic competence. PLoS Genetics. 18(6). e1010271–e1010271. 9 indexed citations
7.
Han, Yan, Yeran Yang, Jun Yan, et al.. (2021). Loss of the wild-type KRAS allele promotes pancreatic cancer progression through functional activation of YAP1. Oncogene. 40(50). 6759–6771. 17 indexed citations
8.
Sinha, Sanju, Karina Barbosa, Kuoyuan Cheng, et al.. (2021). A systematic genome-wide mapping of oncogenic mutation selection during CRISPR-Cas9 genome editing. Nature Communications. 12(1). 6512–6512. 34 indexed citations
9.
Takai, Atsushi, Hien Dang, Naoki Oishi, et al.. (2019). Genome-Wide RNAi Screen Identifies PMPCB as a Therapeutic Vulnerability in EpCAM+ Hepatocellular Carcinoma. Cancer Research. 79(9). 2379–2391. 23 indexed citations
10.
Brown, Zachary J., Qiong Fu, Chi Ma, et al.. (2018). Carnitine palmitoyltransferase gene upregulation by linoleic acid induces CD4+ T cell apoptosis promoting HCC development. Cell Death and Disease. 9(6). 620–620. 107 indexed citations
11.
Thomas, Anish, Yuanbin Chen, Seth M. Steinberg, et al.. (2015). High mesothelin expression in advanced lung adenocarcinoma is associated withKRASmutations and a poor prognosis. Oncotarget. 6(13). 11694–11703. 65 indexed citations
12.
Yuan, Tina L., Christof Fellmann, Chih-Shia Lee, et al.. (2014). Development of siRNA Payloads to Target KRAS -Mutant Cancer. Cancer Discovery. 4(10). 1182–1197. 93 indexed citations
13.
Wang, Yue, et al.. (2014). Long-term outcome after surgical resection for cholangiocarcinoma and prognostic index value. The Surgeon. 14(1). 38–43. 4 indexed citations
14.
Taniguchi, Cullen M., Jonathon N. Winnay, Tatsuya Kondo, et al.. (2010). The Phosphoinositide 3-Kinase Regulatory Subunit p85α Can Exert Tumor Suppressor Properties through Negative Regulation of Growth Factor Signaling. Cancer Research. 70(13). 5305–5315. 125 indexed citations
15.
Taniguchi, Cullen M., Jonathon N. Winnay, Tatsuya Kondo, et al.. (2010). The Phosphoinositide 3-Kinase Regulatory Subunit p85 Can Exert Tumor Suppressor Properties through Negative Regulation of Growth Factor Signaling. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations
16.
Hill, Jennifer W., Yong Xu, Frédéric Preitner, et al.. (2009). Phosphatidyl Inositol 3-Kinase Signaling in Hypothalamic Proopiomelanocortin Neurons Contributes to the Regulation of Glucose Homeostasis. Endocrinology. 150(11). 4874–4882. 75 indexed citations
17.
Schlabach, Michael R., Ji Luo, Nicole L. Solimini, et al.. (2008). Cancer Proliferation Gene Discovery Through Functional Genomics. Science. 319(5863). 620–624. 291 indexed citations
18.
Smogorzewska, Agata, Shuhei Matsuoka, Patrizia Vinciguerra, et al.. (2007). Identification of the FANCI Protein, a Monoubiquitinated FANCD2 Paralog Required for DNA Repair. Cell. 129(2). 289–301. 552 indexed citations breakdown →
19.
Luo, Ji, et al.. (2006). Loss of class IA PI3K signaling in muscle leads to impaired muscle growth, insulin response, and hyperlipidemia. Cell Metabolism. 3(5). 355–366. 97 indexed citations
20.
Luo, Ji & Lewis C. Cantley. (2005). Then Negative Regulation of Phosphoinositide 3-Kinase Signaling by p85 and Its Implication in Cancer. Cell Cycle. 4(10). 1309–1312. 79 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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