David Liu

23.3k total citations · 6 hit papers
148 papers, 8.0k citations indexed

About

David Liu is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, David Liu has authored 148 papers receiving a total of 8.0k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 51 papers in Oncology and 29 papers in Cancer Research. Recurrent topics in David Liu's work include Cancer Immunotherapy and Biomarkers (22 papers), Cancer Genomics and Diagnostics (18 papers) and CAR-T cell therapy research (18 papers). David Liu is often cited by papers focused on Cancer Immunotherapy and Biomarkers (22 papers), Cancer Genomics and Diagnostics (18 papers) and CAR-T cell therapy research (18 papers). David Liu collaborates with scholars based in United States, Germany and China. David Liu's co-authors include Michael Baseler, Da Wei Huang, Yongjian Guo, Brad T. Sherman, H. Clifford Lane, Richard A. Lempicki, Liliana Ossowski, David Bryant, Robert M. Stephens and Andrew V. Anzalone and has published in prestigious journals such as Nature, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

David Liu

135 papers receiving 7.8k citations

Hit Papers

DAVID Bioinformatics Resources: expanded annotation datab... 2007 2026 2013 2019 2007 2021 2021 2019 2021 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Liu United States 38 4.4k 1.5k 1.4k 893 813 148 8.0k
Fan Bai China 44 3.6k 0.8× 1.1k 0.7× 1.3k 0.9× 566 0.6× 900 1.1× 177 6.9k
Paolo Fortina United States 47 4.7k 1.1× 1.4k 0.9× 1.9k 1.3× 576 0.6× 875 1.1× 208 9.2k
Stefan Wiemann Germany 51 5.8k 1.3× 1.2k 0.8× 2.1k 1.4× 778 0.9× 753 0.9× 186 8.8k
Alexander D. Borowsky United States 51 4.7k 1.1× 2.6k 1.7× 1.6k 1.1× 1.1k 1.3× 663 0.8× 197 8.7k
Carlos S. Moreno United States 50 4.1k 0.9× 1.3k 0.9× 1.6k 1.1× 1.3k 1.4× 685 0.8× 146 7.3k
Mitchell Stark Australia 27 5.1k 1.2× 1.2k 0.8× 1.3k 0.9× 716 0.8× 754 0.9× 65 7.5k
Dan Mercola United States 55 6.0k 1.4× 2.0k 1.3× 1.4k 1.0× 865 1.0× 755 0.9× 130 8.4k
Anthony D. Whetton United Kingdom 52 5.2k 1.2× 1.4k 0.9× 1.0k 0.7× 1.2k 1.4× 460 0.6× 277 8.9k
Connie R. Jiménez Netherlands 56 4.8k 1.1× 1.3k 0.9× 1.4k 0.9× 655 0.7× 536 0.7× 240 8.6k
Jiang Qian United States 61 7.9k 1.8× 1.2k 0.8× 1.2k 0.8× 805 0.9× 880 1.1× 300 12.4k

Countries citing papers authored by David Liu

Since Specialization
Citations

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

Fields of papers citing papers by David Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Liu

This figure shows the co-authorship network connecting the top 25 collaborators of David Liu. A scholar is included among the top collaborators of David Liu 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 David Liu. David Liu 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.
Daliri, Karim, Jürgen Hescheler, Gregory A. Newby, et al.. (2025). Modulating Collagen I Expression in Fibroblasts by CRISPR-Cas9 Base Editing of the Collagen 1A1 Promoter. International Journal of Molecular Sciences. 26(7). 3041–3041. 3 indexed citations
2.
Wan, Guihong, Zoltan Maliga, Tuulia Vallius, et al.. (2024). SpatialCells: automated profiling of tumor microenvironments with spatially resolved multiplexed single-cell data. Briefings in Bioinformatics. 25(3). 2 indexed citations
4.
Buchbinder, Elizabeth I., Justine V. Cohen, Giuseppe Tarantino, et al.. (2024). A Phase II Study of ERK Inhibition by Ulixertinib (BVD-523) in Metastatic Uveal Melanoma. Cancer Research Communications. 4(5). 1321–1327. 7 indexed citations
5.
Kosnopfel, Corinna, D. S. Faber, Andreas Schlösser, et al.. (2024). Loss of p14 diminishes immunogenicity in melanoma via non‐canonical Wnt signaling by reducing the peptide surface density. Molecular Oncology. 18(10). 2449–2470. 1 indexed citations
6.
Giobbie‐Hurder, Anita, Miklos C. Fogarasi, Patrick A. Ott, et al.. (2024). Nivolumab maintenance improves overall survival of patients with advanced melanoma who experience severe immune-related adverse events on nivolumab plus ipilimumab. Journal for ImmunoTherapy of Cancer. 12(8). e009061–e009061. 5 indexed citations
7.
Sharkey, Aidan, et al.. (2024). Aortic Valve Replacement. JACC Case Reports. 29(8). 102278–102278.
8.
Khaddour, Karam, Rizwan Haq, Elizabeth I. Buchbinder, et al.. (2024). Targeting RAF1 gene fusions with MEK inhibition in metastatic melanoma. The Oncologist. 30(3).
9.
Gerstung, Moritz, David Liu, Marzyeh Ghassemi, et al.. (2024). Artificial intelligence. Cancer Cell. 42(6). 915–918. 6 indexed citations
10.
Łaczmański, Łukasz, et al.. (2023). P07 Optimizing DNA specificity and applicability of base and prime editors on COL7A1 variants causing recessive dystrophic epidermolysis bullosa. British Journal of Dermatology. 189(1). e16–e17. 1 indexed citations
11.
Menéndez, David, et al.. (2022). Like mother, like daughter: Adults’ judgments about genetic inheritance.. Journal of Experimental Psychology Applied. 29(1). 63–77. 3 indexed citations
12.
Cheng, Michael L., Jessica Lee, Rachit Kumar, et al.. (2022). Response to MEK Inhibitor Therapy inMAP2K1(MEK1) K57N Non–Small-Cell Lung Cancer and Genomic Landscape ofMAP2K1Mutations in Non–Small-Cell Lung Cancer. JCO Precision Oncology. 6(6). e2200382–e2200382. 4 indexed citations
13.
Nelson, James W., Peyton B. Randolph, Simon P. Shen, et al.. (2021). Engineered pegRNAs improve prime editing efficiency. Nature Biotechnology. 40(3). 402–410. 463 indexed citations breakdown →
14.
Gurjao, Carino, David Liu, Matan Hofree, et al.. (2019). Intrinsic Resistance to Immune Checkpoint Blockade in a Mismatch Repair–Deficient Colorectal Cancer. Cancer Immunology Research. 7(8). 1230–1236. 60 indexed citations
15.
Kamran, Sophia C., Jochen K. Lennerz, Claire A. Margolis, et al.. (2019). Integrative Molecular Characterization of Resistance to Neoadjuvant Chemoradiation in Rectal Cancer. Clinical Cancer Research. 25(18). 5561–5571. 62 indexed citations
16.
Schwartzberg, Lee S., Edward S. Kim, David Liu, & Deborah Schrag. (2017). Precision Oncology: Who, How, What, When, and When Not?. American Society of Clinical Oncology Educational Book. 37(37). 160–169. 166 indexed citations
17.
Bourne, Gregory T., Li Zhao, Ashok Bhandari, et al.. (2017). Hepcidin Mimetic Ptg-300 for Treatment of Ineffective Erythropoiesis and Iron Overload. American Journal of Hematology. 92(8). 3 indexed citations
18.
Horak, Christine E., Lajos Pusztai, Guan Xing, et al.. (2013). Biomarker Analysis of Neoadjuvant Doxorubicin/Cyclophosphamide Followed by Ixabepilone or Paclitaxel in Early-Stage Breast Cancer. Clinical Cancer Research. 19(6). 1587–1595. 83 indexed citations
19.
Zhang, Yi, Yan Cheng, Xingcong Ren, et al.. (2012). Dysfunction of Nucleus Accumbens-1 Activates Cellular Senescence and Inhibits Tumor Cell Proliferation and Oncogenesis. Cancer Research. 72(16). 4262–4275. 29 indexed citations
20.
Harlan, John M. & David Liu. (1992). Adhesion : its role in inflammatory disease. 148 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026