Xiangju Kong

16.8k total citations · 6 hit papers
20 papers, 5.1k citations indexed

About

Xiangju Kong is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Xiangju Kong has authored 20 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 11 papers in Oncology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Xiangju Kong's work include Melanoma and MAPK Pathways (15 papers), Computational Drug Discovery Methods (5 papers) and HER2/EGFR in Cancer Research (4 papers). Xiangju Kong is often cited by papers focused on Melanoma and MAPK Pathways (15 papers), Computational Drug Discovery Methods (5 papers) and HER2/EGFR in Cancer Research (4 papers). Xiangju Kong collaborates with scholars based in United States, Australia and China. Xiangju Kong's co-authors include Roger S. Lo, Antoni Ribas, Hubing Shi, Jeffrey A. Sosman, Richard C. Koya, Thinle Chodon, Gatien Moriceau, Stanley F. Nelson, Hane Lee and Mi‐Kyung Lee and has published in prestigious journals such as Nature, Cell and Angewandte Chemie International Edition.

In The Last Decade

Xiangju Kong

19 papers receiving 5.1k citations

Hit Papers

Melanomas acquire resistance to B-RAF(V600E) inhibition b... 2010 2026 2015 2020 2010 2013 2012 2014 2015 500 1000 1.5k
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. Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation
    2010 1.6k citations Ramin Nazarian, Hubing Shi et al. Nature profile →
  2. Acquired Resistance and Clonal Evolution in Melanoma during BRAF Inhibitor Therapy
    2013 715 citations Hubing Shi, Willy Hugo et al. Cancer Discovery profile →
  3. Melanoma whole-exome sequencing identifies V600EB-RAF amplification-mediated acquired B-RAF inhibitor resistance
    2012 470 citations Hubing Shi, Gatien Moriceau et al. Nature Communications profile →
  4. Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma
    2014 427 citations Judith M. Müller, Oscar Krijgsman et al. Nature Communications profile →
  5. Non-genomic and Immune Evolution of Melanoma Acquiring MAPKi Resistance
    2015 412 citations Willy Hugo, Hubing Shi et al. Cell profile →
  6. Therapy-induced tumour secretomes promote resistance and tumour progression
    2015 364 citations Anna C. Obenauf, Yilong Zou et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiangju Kong United States 16 4.1k 2.7k 779 708 660 20 5.1k
Thinle Chodon United States 22 3.3k 0.8× 3.2k 1.2× 578 0.7× 1.4k 1.9× 527 0.8× 33 5.2k
Dennie T. Frederick United States 32 3.8k 0.9× 3.2k 1.2× 414 0.5× 1.7k 2.4× 497 0.8× 79 6.2k
Willy Hugo United States 20 2.5k 0.6× 2.4k 0.9× 334 0.4× 1.4k 2.0× 369 0.6× 44 4.3k
Dan Niculescu‐Duvaz United Kingdom 21 3.3k 0.8× 1.6k 0.6× 611 0.8× 239 0.3× 636 1.0× 35 4.1k
Nathalie Dhomen United Kingdom 19 2.2k 0.5× 1.6k 0.6× 318 0.4× 474 0.7× 375 0.6× 34 3.2k
Kimberly B. Dahlman United States 21 2.3k 0.6× 1.7k 0.6× 401 0.5× 451 0.6× 488 0.7× 38 3.2k
Gatien Moriceau United States 21 2.2k 0.5× 1.5k 0.5× 395 0.5× 412 0.6× 360 0.5× 25 2.8k
Kathryn Packman United States 28 2.6k 0.6× 2.2k 0.8× 187 0.2× 286 0.4× 399 0.6× 65 3.9k
Amaya Virós United Kingdom 21 2.1k 0.5× 1.6k 0.6× 222 0.3× 459 0.6× 198 0.3× 46 3.3k
Steven R. Whittaker United Kingdom 20 2.3k 0.6× 1.4k 0.5× 416 0.5× 177 0.3× 515 0.8× 28 3.2k

Countries citing papers authored by Xiangju Kong

Since Specialization
Citations

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

Fields of papers citing papers by Xiangju Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiangju Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Xiangju Kong. A scholar is included among the top collaborators of Xiangju Kong 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 Xiangju Kong. Xiangju Kong 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.
Kong, Xiangju, et al.. (2024). Flow-Sediment Interaction and Formation Mechanism of Sediment Longitudinal Streaky Structures in Rough Channel Flows. Journal of Hydraulic Engineering. 151(1). 1 indexed citations
2.
Song, Chunying, Marco Piva, Lu Sun, et al.. (2017). Recurrent Tumor Cell–Intrinsic and –Extrinsic Alterations during MAPKi-Induced Melanoma Regression and Early Adaptation. Cancer Discovery. 7(11). 1248–1265. 109 indexed citations
3.
Titz, Bjoern, Anastasia Lomova, Willy Hugo, et al.. (2016). JUN dependency in distinct early and late BRAF inhibition adaptation states of melanoma. Cell Discovery. 2(1). 43 indexed citations
4.
Johnson, Douglas B., Alexander M. Menzies, Lisa Zimmer, et al.. (2015). BRAF inhibitor acquired resistance: A multicenter meta-analysis of the spectrum and clinical implications of resistance mechanisms.. Journal of Clinical Oncology. 33(15_suppl). 9008–9008. 2 indexed citations
5.
Obenauf, Anna C., Yilong Zou, Andrew L. Ji, et al.. (2015). Therapy-induced tumour secretomes promote resistance and tumour progression. Nature. 520(7547). 368–372. 364 indexed citations breakdown →
6.
Hugo, Willy, Hubing Shi, Lu Sun, et al.. (2015). Non-genomic and Immune Evolution of Melanoma Acquiring MAPKi Resistance. Cell. 162(6). 1271–1285. 412 indexed citations breakdown →
7.
Moriceau, Gatien, Willy Hugo, Aayoung Hong, et al.. (2015). Tunable-Combinatorial Mechanisms of Acquired Resistance Limit the Efficacy of BRAF/MEK Cotargeting but Result in Melanoma Drug Addiction. Cancer Cell. 27(2). 240–256. 237 indexed citations
8.
Müller, Judith M., Oscar Krijgsman, Jennifer Tsoi, et al.. (2014). Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma. Nature Communications. 5(1). 5712–5712. 427 indexed citations breakdown →
9.
Marusiak, Anna A., Willy Hugo, Eleanor W. Trotter, et al.. (2014). Mixed lineage kinases activate MEK independently of RAF to mediate resistance to RAF inhibitors. Nature Communications. 5(1). 3901–3901. 63 indexed citations
10.
Shi, Hubing, Aayoung Hong, Xiangju Kong, et al.. (2013). A Novel AKT1 Mutant Amplifies an Adaptive Melanoma Response to BRAF Inhibition. Cancer Discovery. 4(1). 69–79. 133 indexed citations
11.
Shi, Hubing, Willy Hugo, Xiangju Kong, et al.. (2013). Acquired Resistance and Clonal Evolution in Melanoma during BRAF Inhibitor Therapy. Cancer Discovery. 4(1). 80–93. 715 indexed citations breakdown →
12.
Hou, Shuang, Libo Zhao, Qinglin Shen, et al.. (2013). Polymer Nanofiber‐Embedded Microchips for Detection, Isolation, and Molecular Analysis of Single Circulating Melanoma Cells. Angewandte Chemie International Edition. 52(12). 3379–3383. 182 indexed citations
13.
Hou, Shuang, Libo Zhao, Qinglin Shen, et al.. (2013). Polymer Nanofiber‐Embedded Microchips for Detection, Isolation, and Molecular Analysis of Single Circulating Melanoma Cells. Angewandte Chemie. 125(12). 3463–3467. 21 indexed citations
14.
Shi, Hubing, Gatien Moriceau, Xiangju Kong, et al.. (2012). Preexisting MEK1 Exon 3 Mutations in V600E/K BRAF Melanomas Do Not Confer Resistance to BRAF Inhibitors. Cancer Discovery. 2(5). 414–424. 75 indexed citations
15.
Shi, Hubing, Gatien Moriceau, Xiangju Kong, et al.. (2012). Melanoma whole-exome sequencing identifies V600EB-RAF amplification-mediated acquired B-RAF inhibitor resistance. Nature Communications. 3(1). 724–724. 470 indexed citations breakdown →
16.
Shi, Hubing, Xiangju Kong, Antoni Ribas, & Roger S. Lo. (2011). Combinatorial Treatments That Overcome PDGFRβ-Driven Resistance of Melanoma Cells to V600EB-RAF Inhibition. Cancer Research. 71(15). 5067–5074. 184 indexed citations
17.
Nazarian, Ramin, Roberto Ferrari, Xiangju Kong, Siavash K. Kurdistani, & Roger S. Lo. (2011). Abstract 714: A potential epigenetic regulation of PDGFRβ overexpression in melanomas acquiring resistance to PLX4032. Cancer Research. 71(8_Supplement). 714–714. 1 indexed citations
18.
Nazarian, Ramin, Hubing Shi, Qi Wang, et al.. (2010). Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation. Nature. 468(7326). 973–977. 1614 indexed citations breakdown →
19.
Zhang, Zuoming, et al.. (2005). Overexpression and characterization of a lipase from Bacillus subtilis. Protein Expression and Purification. 45(1). 22–29. 84 indexed citations
20.
Wang, Shiyu, et al.. (2002). [Characteristics and application of thermophilic enzymes].. PubMed. 42(2). 259–62.

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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