Zhaoshi Bao

5.4k total citations · 1 hit paper
64 papers, 2.6k citations indexed

About

Zhaoshi Bao is a scholar working on Cancer Research, Molecular Biology and Genetics. According to data from OpenAlex, Zhaoshi Bao has authored 64 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Cancer Research, 34 papers in Molecular Biology and 32 papers in Genetics. Recurrent topics in Zhaoshi Bao's work include Glioma Diagnosis and Treatment (32 papers), MicroRNA in disease regulation (21 papers) and Cancer-related molecular mechanisms research (19 papers). Zhaoshi Bao is often cited by papers focused on Glioma Diagnosis and Treatment (32 papers), MicroRNA in disease regulation (21 papers) and Cancer-related molecular mechanisms research (19 papers). Zhaoshi Bao collaborates with scholars based in China, United States and Hong Kong. Zhaoshi Bao's co-authors include Tao Jiang, Chuanbao Zhang, Wei Zhang, Zheng Wang, Qiangwei Wang, Ying Zhang, Guanzhang Li, Fan Wu, Gan You and Zheng Zhao and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Zhaoshi Bao

62 papers receiving 2.6k citations

Hit Papers

Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resou... 2021 2026 2022 2024 2021 200 400 600
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. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients
    2021 617 citations Zheng Zhao, Kenan Zhang et al. Genomics Proteomics & Bioinformatics profile →

Peers

Zhaoshi Bao
Fonnet E. Bleeker Netherlands
Olga A. Guryanova United States
Guanzhang Li China
Logan A. Walsh Canada
Remco J. Molenaar Netherlands
Gaspar J. Kitange United States
Anjan Misra United States
Ruichao Chai China
Armida W. M. Fabius Netherlands
Fonnet E. Bleeker Netherlands
Zhaoshi Bao
Citations per year, relative to Zhaoshi Bao Zhaoshi Bao (= 1×) peers Fonnet E. Bleeker

Countries citing papers authored by Zhaoshi Bao

Since Specialization
Citations

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

Fields of papers citing papers by Zhaoshi Bao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhaoshi Bao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhaoshi Bao. A scholar is included among the top collaborators of Zhaoshi Bao 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 Zhaoshi Bao. Zhaoshi Bao 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
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Li, Guanzhang, Jing Feng, Fan Wu, et al.. (2023). Stalled oligodendrocyte differentiation in IDH-mutant gliomas. Genome Medicine. 15(1). 24–24. 18 indexed citations
4.
Yang, Ying, Hongwei Wang, Zhaoshi Bao, et al.. (2022). An Optimized Proteomics Approach Reveals Novel Alternative Proteins in Mouse Liver Development. Molecular & Cellular Proteomics. 22(1). 100480–100480. 7 indexed citations
5.
Zhao, Zheng, Kenan Zhang, Qiangwei Wang, et al.. (2021). Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients. Genomics Proteomics & Bioinformatics. 19(1). 1–12. 617 indexed citations breakdown →
6.
Bao, Zhaoshi, Yongzhi Wang, Qiangwei Wang, et al.. (2021). Intratumor heterogeneity, microenvironment, and mechanisms of drug resistance in glioma recurrence and evolution. Frontiers of Medicine. 15(4). 551–561. 59 indexed citations
7.
Sun, Lihua, Yiping Wu, Zheng Wang, et al.. (2016). Overexpression of Paxillin Correlates with Tumor Progression and Predicts Poor Survival in Glioblastoma. CNS Neuroscience & Therapeutics. 23(1). 69–75. 32 indexed citations
8.
Zhang, Wenlong, Yanwei Liu, Huimin Hu, et al.. (2015). ALDH1A3: A Marker of Mesenchymal Phenotype in Gliomas Associated with Cell Invasion. PLoS ONE. 10(11). e0142856–e0142856. 34 indexed citations
9.
Cheng, Wen, Mingyang Li, Jinquan Cai, et al.. (2015). HDAC4, a prognostic and chromosomal instability marker, refines the predictive value of MGMT promoter methylation. Journal of Neuro-Oncology. 122(2). 303–312. 33 indexed citations
10.
Han, Lei, Junxia Zhang, Liang Zeng, et al.. (2014). AJAP1 is Dysregulated at an Early Stage of Gliomagenesis and Suppresses Invasion Through Cytoskeleton Reorganization. CNS Neuroscience & Therapeutics. 20(5). 429–437. 24 indexed citations
11.
Zhang, Chunlong, Chunquan Li, Jing Li, et al.. (2014). Identification of miRNA-Mediated Core Gene Module for Glioma Patient Prediction by Integrating High-Throughput miRNA, mRNA Expression and Pathway Structure. PLoS ONE. 9(5). e96908–e96908. 23 indexed citations
12.
Bao, Zhaoshi, Hongjun Wang, Chuanbao Zhang, et al.. (2014). Integrated analysis using methylation and gene expression microarrays reveals PDE4C as a prognostic biomarker in human glioma. Oncology Reports. 32(1). 250–260. 15 indexed citations
13.
Wang, Zheng, Zhaoshi Bao, Wei Yan, et al.. (2014). SOCS3 Promoter Hypermethylation Is a Favorable Prognosticator and a Novel Indicator for G-CIMP-Positive GBM Patients. PLoS ONE. 9(3). e91829–e91829. 17 indexed citations
14.
Wang, Zheng, Zhaoshi Bao, Wei Yan, et al.. (2013). Isocitrate dehydrogenase 1 (IDH1) mutation-specific microRNA signature predicts favorable prognosis in glioblastoma patients with IDH1 wild type. Journal of Experimental & Clinical Cancer Research. 32(1). 59–59. 40 indexed citations
15.
Zhang, Chuanbao, Zhaoshi Bao, Wei Zhang, & Tao Jiang. (2013). Progress on molecular biomarkers and classification of malignant gliomas. Frontiers of Medicine. 7(2). 150–156. 16 indexed citations
16.
Bao, Zhaoshi, et al.. (2013). Whole‐Genome mRNA Expression Profiling Identifies Functional and Prognostic Signatures in Patients with Mesenchymal Glioblastoma Multiforme. CNS Neuroscience & Therapeutics. 19(9). 714–720. 25 indexed citations
17.
Bao, Zhaoshi, et al.. (2013). Epigenetic silencing of KAZALD1 confers a better prognosis and is associated with malignant transformation/progression in glioma. Oncology Reports. 30(5). 2089–2096. 18 indexed citations
18.
Yan, Wei, Wei Zhang, Gan You, et al.. (2012). Correlation of IDH1 Mutation with Clinicopathologic Factors and Prognosis in Primary Glioblastoma: A Report of 118 Patients from China. PLoS ONE. 7(1). e30339–e30339. 114 indexed citations
19.
Wang, Yujie, Shouwei Li, Lü Chen, et al.. (2012). Glioblastoma with an oligodendroglioma component: distinct clinical behavior, genetic alterations, and outcome. Neuro-Oncology. 14(4). 518–525. 59 indexed citations
20.
Huang, Lei, Pei Yang, Wensheng Zhang, et al.. (2011). Clinical and molecular genetic factors affecting postoperative seizure control of 183 Chinese adult patients with low‐grade gliomas. European Journal of Neurology. 19(2). 298–306. 38 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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