Yingcong Wang
Impact in
- Geriatrics and Gerontology top 10%
Papers in
-
- PI3K/AKT/mTOR signaling in cancer 5
- Ubiquitin and proteasome pathways 4
- Histone Deacetylase Inhibitors Research 3
- Cancer therapeutics and mechanisms 3
- Hematology 13
- Multiple Myeloma Research and Treatments 10
- Co-authors
- Fengpeng Zhang (1 shared paper)Junwei Sun (12 shared papers)Yanfeng Wang (11 shared papers)Dong Guo (3 shared papers)Kai Cai (1 shared paper)Yang Bai (1 shared paper)Jumei Shi (18 shared papers)Zhenggang Ren (4 shared papers)
In The Last Decade
Yingcong Wang
49 papers receiving 792 citations
Peers
Comparison fields: 5 of 130
- Geriatrics and Gerontology 27
- Cancer Research 86
- Hematology 60
- Cell Biology 83
- Oncology 114
Countries citing papers authored by Yingcong Wang
This map shows the geographic impact of Yingcong Wang'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 Yingcong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingcong Wang more than expected).
Fields of papers citing papers by Yingcong Wang
This network shows the impact of papers produced by Yingcong Wang. 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 Yingcong Wang. The network helps show where Yingcong Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yingcong Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 96 | |
| 2 | 2018 | 78 | |
| 3 | 2019 | 65 | |
| 4 | 2018 | 62 | |
| 5 | 2013 | 53 | |
| 6 | 2017 | 43 | |
| 7 | 2021 | 43 | |
| 8 | 2024 | 41 | |
| 9 | 2019 | 28 | |
| 10 | 2022 | 28 | |
| 11 | 2018 | 22 | |
| 12 | 2023 | 18 | |
| 13 | 2020 | 17 | |
| 14 | 2018 | 15 | |
| 15 | 2022 | 15 | |
| 16 | 2018 | 15 | |
| 17 | 2022 | 15 | |
| 18 | Over expression of hyaluronan promotes progression of HCC via CD44-mediated pyruvate kinase M2 nuclear translocation. | 2016 | 14 |
| 19 | Dynamin2 downregulation delays EGFR endocytic trafficking and promotes EGFR signaling and invasion in hepatocellular carcinoma. | 2015 | 13 |
| 20 | 2022 | 10 |
About Yingcong Wang
Yingcong Wang is a scholar working on Molecular Biology, Hematology, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Pathology and Forensic Medicine, having authored 51 papers that have together received 802 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (10 papers), Advanced Memory and Neural Computing (10 papers), Neuroscience and Neural Engineering (5 papers), PI3K/AKT/mTOR signaling in cancer (5 papers), Ubiquitin and proteasome pathways (4 papers), Lymphoma Diagnosis and Treatment (3 papers), Histone Deacetylase Inhibitors Research (3 papers) and Cancer therapeutics and mechanisms (3 papers). The work is most often cited by research in Geriatrics and Gerontology (27 citations), Cancer Research (86 citations), Hematology (60 citations), Cell Biology (83 citations) and Oncology (114 citations). Yingcong Wang has collaborated with scholars based in China, Australia and Malaysia. Frequent co-authors include Fengpeng Zhang, Junwei Sun, Yanfeng Wang, Dong Guo, Kai Cai, Yang Bai, Jumei Shi, Zhenggang Ren, Xiaosong Wu and Zhaoning Gong. Their work appears in journals such as Acta Biochimica et Biophysica Sinica, Cancer Letters, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Industrial Informatics and IEEE Internet of Things Journal.
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.