🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Kun Wang

Jiangsu University

ORCID: 0000-0001-9851-7080

Also affiliated with Weifang Medical University, Guangzhou University of Chinese Medicine, Xuzhou Medical College, Soochow University, Peking University, Tianjin Medical University Cancer Institute and Hospital, Second Hospital of Shandong University, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Affiliated Hospital of Jiangsu University, Lanzhou University Second Hospital, Shanghai East Hospital, Peking University Third Hospital, Guangdong Academy of Medical Sciences, Ministry of Education, Pingjin Hospital, Southern Medical University, Lanzhou University

Biochemistry, Genetics and Molecular BiologyMedicine

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile
0Author DataRank

Indexed papers

2in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 2 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Papers

Driven by 6 papers. Top paper: “Iron chelators loaded on myocardiocyte mitochondria-targeted nanozyme system for treating myocardial ischemia-reperfusion injury in mouse models”.

Iron chelators loaded on myocardiocyte mitochondria-targeted nanozyme system for treating myocardial ischemia-reperfusion injury in mouse models

Journal of Nanobiotechnology(2025)10.1186/s12951-025-03197-1
N/A
0.793DataRank · unranked
48 citations

Kun Wang, Rongting Zhang, Ziyang Zhu, Wenyuan Wang, Biao Yang +3 more

Longitudinal MRI-based fusion novel model predicts pathological complete response in breast cancer treated with neoadjuvant chemotherapy: a multicenter, retrospective study

eClinicalMedicine(2023)10.1016/j.eclinm.2023.101899
N/A
0.766DataRank · unranked
164 citations

Teng Zhu, XiaoLing Zhang, Wei Li, XingXing Zheng, MinYi Cheng +8 more

Comp34 displays potent preclinical antitumor efficacy in triple-negative breast cancer via inhibition of NUDT3-AS4, a novel oncogenic long noncoding RNA

Cell Death and Disease(2020)10.1038/s41419-020-03235-w
N/A
0DataRank · unranked
20 citations

Piwen Wang, Pranabananda Dutta, Seyung Chung, Qun Li, Kun Wang +14 more

Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.09.20.558683
N/A
0DataRank · unranked
2 citations

Binbin Wang, Di Wu, Saugato Rahman Dhruba, Matthew Nagy, Sushant Patkar +4 more

Decoupling the correlation between cytotoxic and exhausted T lymphocyte transcriptomic signatures enhances melanoma immunotherapy response prediction from tumor expression

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.01.17.524482
N/A
0DataRank · unranked
0 citations

Kun Wang, Peng Jiang, Eytan Ruppin, Binbin Wang

Wip1 phosphatase activator QGC-8–52 specifically sensitizes p53-negative cancer cells to chemotherapy while protecting normal cells

Drug Resistance Updates(2024)10.1016/j.drup.2024.101196
N/A
0DataRank · unranked
6 citations

Xiaoxiao Ge, Xiao-xiao Ge, Jieqing Li, Kun Wang, Qiao‐Hong Chen +5 more