Jinzi J. Wu

1.7k total citations
41 papers, 1.2k citations indexed

About

Jinzi J. Wu is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jinzi J. Wu has authored 41 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 16 papers in Oncology and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jinzi J. Wu's work include Monoclonal and Polyclonal Antibodies Research (9 papers), Peptidase Inhibition and Analysis (6 papers) and Chemical Synthesis and Analysis (6 papers). Jinzi J. Wu is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (9 papers), Peptidase Inhibition and Analysis (6 papers) and Chemical Synthesis and Analysis (6 papers). Jinzi J. Wu collaborates with scholars based in United States, Canada and China. Jinzi J. Wu's co-authors include Kit S. Lam, Yunching Chen, Leaf Huang, Qiang Lou, Seema V. Garde, Fahad Al‐Obeidi, Chandra J. Panchal, Matthew A. Sills, Quynhchi Pham and Shafaat A. Rabbani and has published in prestigious journals such as Blood, Nature Biotechnology and Hepatology.

In The Last Decade

Jinzi J. Wu

40 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jinzi J. Wu United States 16 777 214 175 156 151 41 1.2k
Clifford Longley United States 20 620 0.8× 187 0.9× 219 1.3× 193 1.2× 154 1.0× 39 1.3k
Milan Fábry Czechia 21 750 1.0× 309 1.4× 184 1.1× 164 1.1× 160 1.1× 82 1.3k
Andrew Mountain United Kingdom 21 1.3k 1.6× 390 1.8× 467 2.7× 103 0.7× 55 0.4× 31 1.9k
Jason E. Hudak United States 11 1.1k 1.5× 239 1.1× 241 1.4× 477 3.1× 61 0.4× 16 1.6k
Weirong Yuan United States 20 1.2k 1.6× 162 0.8× 422 2.4× 364 2.3× 40 0.3× 36 1.6k
Edelmira Cabezas United States 12 1.1k 1.5× 271 1.3× 114 0.7× 148 0.9× 80 0.5× 13 1.7k
N.S. Pannu Netherlands 8 709 0.9× 141 0.7× 66 0.4× 324 2.1× 104 0.7× 10 1.2k
Jarrett Adams Canada 24 1.1k 1.4× 368 1.7× 391 2.2× 73 0.5× 60 0.4× 53 1.9k
C. Ronald Geyer Canada 25 1.2k 1.6× 396 1.9× 237 1.4× 73 0.5× 43 0.3× 68 1.7k
Joseph P. Davide United States 22 1.3k 1.6× 163 0.8× 461 2.6× 132 0.8× 392 2.6× 37 2.1k

Countries citing papers authored by Jinzi J. Wu

Since Specialization
Citations

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

Fields of papers citing papers by Jinzi J. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jinzi J. Wu. 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 Jinzi J. Wu. The network helps show where Jinzi J. Wu may publish in the future.

Co-authorship network of co-authors of Jinzi J. Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jinzi J. Wu. A scholar is included among the top collaborators of Jinzi J. Wu 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 Jinzi J. Wu. Jinzi J. Wu 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.
2.
Xiang, Leihong, Rixin Chen, Liming Wu, et al.. (2024). 49342 First FASN inhibitor ASC40 to treat acne vulgaris patients: final results form a Phase 2 trial. Journal of the American Academy of Dermatology. 91(3). AB217–AB217. 3 indexed citations
3.
Wu, Jinzi J. & Handan He. (2022). Abstract 5529: In vivo efficacy evaluation of ASC61, an oral PD-L1 inhibitor, in two tumor mouse models. Cancer Research. 82(12_Supplement). 5529–5529. 2 indexed citations
4.
Chen, Hongyi, Zhicheng Zhang, Zhihua Huang, et al.. (2020). First clinical study using HCV protease inhibitor danoprevir to treat COVID-19 patients. Medicine. 99(48). e23357–e23357. 79 indexed citations
5.
Kao, Jia‐Horng, Ming‐Lung Yu, Chi‐Yi Chen, et al.. (2018). Twelve‐week ravidasvir plus ritonavir‐boosted danoprevir and ribavirin for non‐cirrhotic HCV genotype 1 patients: A phase 2 study. Journal of Gastroenterology and Hepatology. 33(8). 1507–1510. 10 indexed citations
6.
Pastorino, Fabio, Daniela Di Paolo, Federica Piccardi, et al.. (2008). Enhanced Antitumor Efficacy of Clinical-Grade Vasculature-Targeted Liposomal Doxorubicin. Clinical Cancer Research. 14(22). 7320–7329. 74 indexed citations
7.
Stranix, Brent R., et al.. (2007). In Vitro Antiviral Activity and Cross-Resistance Profile of PL-100, a Novel Protease Inhibitor of Human Immunodeficiency Virus Type 1. Antimicrobial Agents and Chemotherapy. 51(11). 4036–4043. 23 indexed citations
8.
Garde, Seema V., et al.. (2007). Binding and internalization of NGR-peptide-targeted liposomal doxorubicin (TVT-DOX) in CD13-expressing cells and its antitumor effects. Anti-Cancer Drugs. 18(10). 1189–1200. 73 indexed citations
9.
Stranix, Brent R., et al.. (2006). Lysine sulfonamides as novel HIV-protease inhibitors: Nε-Acyl aromatic α-amino acids. Bioorganic & Medicinal Chemistry Letters. 16(13). 3459–3462. 72 indexed citations
10.
Annabi, Borhane, Jean-Christophe Currie, Hélène Dulude, et al.. (2006). Contribution of the 37-kDa laminin receptor precursor in the anti-metastatic PSP94-derived peptide PCK3145 cell surface binding. Biochemical and Biophysical Research Communications. 346(1). 358–366. 13 indexed citations
11.
Annabi, Borhane, Jean-Christophe Currie, Robert D. Hawkins, et al.. (2005). A PSP94-derived Peptide PCK3145 inhibits MMP-9 Secretion and Triggers CD44 Cell Surface Shedding: Implication in Tumor Metastasis. Clinical & Experimental Metastasis. 22(5). 429–439. 33 indexed citations
12.
Shukeir, Nicholas, Seema V. Garde, Jinzi J. Wu, Chandra J. Panchal, & Shafaat A. Rabbani. (2005). Prostate secretory protein of 94 amino acids (PSP-94) and its peptide (PCK3145) as potential therapeutic modalities for prostate cancer. Anti-Cancer Drugs. 16(10). 1045–1051. 11 indexed citations
13.
Sills, Matthew A., et al.. (2002). Comparison of Assay Technologies for a Tyrosine Kinase Assay Generates Different Results in High Throughput Screening. SLAS DISCOVERY. 7(3). 191–214. 79 indexed citations
14.
15.
Wu, Jinzi J., et al.. (1998). Comparison of the intrinsic kinase activity and substrate specificity of c-Abl and Bcr-Abl. Bioorganic & Medicinal Chemistry Letters. 8(17). 2279–2284. 15 indexed citations
16.
Al‐Obeidi, Fahad, Jinzi J. Wu, & Kit S. Lam. (1998). Protein tyrosine kinases: Structure, substrate specificity, and drug discovery. Biopolymers. 47(3). 197–223. 74 indexed citations
17.
Lam, Kit S., Thomas Sroka, Yu Zhao, et al.. (1998). Application of “one-bead one-compound” combinatorial library methods in signal transduction research. Life Sciences. 62(17-18). 1577–1583. 6 indexed citations
18.
Lou, Qiang, Jinzi J. Wu, Sydney E. Salmon, & Kit S. Lam. (1996). Structure-activity relationship of a novel peptide substrate for p60c-src protein tyrosine kinase. Letters in Peptide Science. 2(5). 289–296. 8 indexed citations
19.
Lam, Kit S., Jinzi J. Wu, & Qiang Lou. (1995). Identification and characterization of a novel synthetic peptide substrate specific for Src‐family protein tyrosine kinases. International journal of peptide & protein research. 45(6). 587–592. 63 indexed citations
20.
Wu, Jinzi J., et al.. (1994). Identifying Substrate Motifs of Protein Kinases by a Random Library Approach. Biochemistry. 33(49). 14825–14833. 84 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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