Brian Lu

2.4k total citations · 1 hit paper
56 papers, 1.6k citations indexed

About

Brian Lu is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Brian Lu has authored 56 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Oncology, 23 papers in Cancer Research and 16 papers in Molecular Biology. Recurrent topics in Brian Lu's work include Pancreatic and Hepatic Oncology Research (27 papers), Cancer Genomics and Diagnostics (22 papers) and Cancer Treatment and Pharmacology (9 papers). Brian Lu is often cited by papers focused on Pancreatic and Hepatic Oncology Research (27 papers), Cancer Genomics and Diagnostics (22 papers) and Cancer Treatment and Pharmacology (9 papers). Brian Lu collaborates with scholars based in United States, Spain and Australia. Brian Lu's co-authors include David Goldstein, Josep Tabernero, Daniel D. Von Hoff, Giampaolo Tortora, Volker Kunzmann, Alfredo Romano, Luís Teixeira, Robert H. El-Maraghi, Jean‐Luc Van Laethem and Salvatore Siena and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Brian Lu

53 papers receiving 1.6k citations

Hit Papers

nab-Paclitaxel Plus Gemcitabine for Metastatic Pancreatic... 2015 2026 2018 2022 2015 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian Lu United States 19 943 510 396 342 322 56 1.6k
Fumiyoshi Fujishima Japan 22 719 0.8× 452 0.9× 273 0.7× 495 1.4× 728 2.3× 195 1.8k
Satoru Moriyama Japan 24 574 0.6× 929 1.8× 245 0.6× 486 1.4× 238 0.7× 82 1.7k
Renê Gerhard Brazil 21 985 1.0× 615 1.2× 365 0.9× 243 0.7× 385 1.2× 41 1.8k
Nagahide Matsubara Japan 27 1.2k 1.2× 944 1.9× 491 1.2× 375 1.1× 485 1.5× 106 2.3k
Klaus J. Schmitz Germany 22 401 0.4× 514 1.0× 297 0.8× 261 0.8× 425 1.3× 51 1.4k
Chan Choi South Korea 24 374 0.4× 603 1.2× 335 0.8× 395 1.2× 347 1.1× 96 1.6k
Takanori Goi Japan 26 712 0.8× 1.2k 2.4× 310 0.8× 207 0.6× 333 1.0× 149 2.1k
Hsuan-Ying Huang Taiwan 30 700 0.7× 1.2k 2.3× 434 1.1× 822 2.4× 429 1.3× 55 2.4k
Jia-Lin Lee South Korea 21 892 0.9× 919 1.8× 344 0.9× 503 1.5× 335 1.0× 50 2.0k
Miki Ohta Japan 20 839 0.9× 980 1.9× 217 0.5× 420 1.2× 395 1.2× 35 1.9k

Countries citing papers authored by Brian Lu

Since Specialization
Citations

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

Fields of papers citing papers by Brian Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Lu. A scholar is included among the top collaborators of Brian Lu 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 Brian Lu. Brian Lu 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.
Bon, Marta, Fraser Cunningham, Brian Lu, et al.. (2025). AI Drug Discovery: Expanding the Horizons of Infectious Disease Therapeutics. ACS Infectious Diseases. 11(8). 2048–2050.
2.
Lu, Brian, David Ha, Sarah Kim, et al.. (2024). Combination Antifungal Therapy for Invasive Mucormycosis in Immunocompromised Hosts: A Single-Center Experience. Open Forum Infectious Diseases. 11(6). ofae103–ofae103. 1 indexed citations
3.
Lu, Brian, Peng Li, Andrew B. Crouse, et al.. (2024). Data-driven Cluster Analysis Reveals Increased Risk for Severe Insulin-deficient Diabetes in Black/African Americans. The Journal of Clinical Endocrinology & Metabolism. 110(2). 387–395. 1 indexed citations
5.
Chang, Amy, et al.. (2023). Electronic phenotyping of community-acquired pneumonia: A tool for inpatient syndrome-specific antimicrobial stewardship. SHILAP Revista de lepidopterología. 3(S2). s114–s115. 1 indexed citations
6.
Lu, Brian, David Ha, J Ferguson, et al.. (2023). 824. Combination Antifungal Therapy for Invasive Mucormycosis in Immunocompromised Hosts: A Single-Center Experience. Open Forum Infectious Diseases. 10(Supplement_2). 1 indexed citations
7.
Awad, Mark M., Brian Lu, Patrick H. Lizotte, et al.. (2021). Selective Histone Deacetylase Inhibitor ACY-241 (Citarinostat) Plus Nivolumab in Advanced Non-Small Cell Lung Cancer: Results From a Phase Ib Study. Frontiers in Oncology. 11. 696512–696512. 33 indexed citations
8.
Lu, Brian, et al.. (2018). Hyperinsulinemic hypoglycemia subtype glucokinase V91L mutant induces necrosis in β-cells via ATP depletion. Biochemistry and Biophysics Reports. 17. 108–113. 1 indexed citations
9.
AhYoung, Andrew P., Brian Lu, Duilio Cascio, & Pascal F. Egea. (2017). Crystal structure of Mdm12 and combinatorial reconstitution of Mdm12/Mmm1 ERMES complexes for structural studies. Biochemical and Biophysical Research Communications. 488(1). 129–135. 20 indexed citations
11.
Tonne, Jason M., Yaxi Zhu, Brian Lu, et al.. (2017). Divergent susceptibilities to AAV-SaCas9-gRNA vector-mediated genome-editing in a single-cell-derived cell population. BMC Research Notes. 10(1). 720–720. 8 indexed citations
12.
Xu, Rui‐Hua, Xianjun Yu, Jihui Hao, et al.. (2017). Efficacy and safety of weekly nab-paclitaxel plus gemcitabine in Chinese patients with metastatic adenocarcinoma of the pancreas: a phase II study. BMC Cancer. 17(1). 885–885. 11 indexed citations
14.
Chiorean, E. Gabriela, Daniel D. Von Hoff, Josep Tabernero, et al.. (2016). Second-line therapy after nab-paclitaxel plus gemcitabine or after gemcitabine for patients with metastatic pancreatic cancer. British Journal of Cancer. 115(2). 188–194. 63 indexed citations
16.
Sakuma, Toshie, Jason M. Tonne, Mahmoud Shaaban Mohamed, et al.. (2015). β-Cell-targeted blockage of PD1 and CTLA4 pathways prevents development of autoimmune diabetes and acute allogeneic islets rejection. Gene Therapy. 22(5). 430–438. 45 indexed citations
17.
Goldstein, David, Robert H. El-Maraghi, Pascal Hammel, et al.. (2015). nab-Paclitaxel Plus Gemcitabine for Metastatic Pancreatic Cancer: Long-Term Survival From a Phase III Trial. JNCI Journal of the National Cancer Institute. 107(2). dju413–dju413. 504 indexed citations breakdown →
19.
Reni, Michele, Daniel D. Von Hoff, E. Gabriela Chiorean, et al.. (2013). CA19-9 Decrease and Kinetics in a Randomized Phase III Trial (MPACT) of Weekly Nab-Paclitaxel Plus Gemcitabine in Metastatic Pancreatic Cancer. Annals of Oncology. 24. iv31–iv31. 2 indexed citations
20.
Lu, Brian, David L. Allen, Leslie A. Leinwand, & Gary E. Lyons. (1999). Spatial and Temporal Changes in Myosin Heavy Chain Gene Expression in Skeletal Muscle Development. Developmental Biology. 216(1). 312–326. 46 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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