Hai Hu
- Molecular Biology top 5%
- Cancer Research top 2%
- Oncology top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Pathology and Forensic Medicine top 5%
- Co-authors
- Frederick SachsCraig D. ShriverEduardo MarbánMichael LiebmanJiao FengCuncun YuanZhen GuoZiliang Jin
- Topics
- Gene expression and cancer classification (13 papers)Cancer-related molecular mechanisms research (12 papers)RNA modifications and cancer (11 papers)
- Journals
- Journal of Clinical OncologySHILAP Revista de lepidopterologíaBioinformatics
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Hai Hu
132 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 153
- Molecular Biology 1.8k
- Cancer Research 791
- Oncology 502
- Cardiology and Cardiovascular Medicine 363
- Pathology and Forensic Medicine 259
Countries citing papers authored by Hai Hu
This map shows the geographic impact of Hai Hu'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 Hai Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai Hu more than expected).
Fields of papers citing papers by Hai Hu
This network shows the impact of papers produced by Hai Hu. 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 Hai Hu. The network helps show where Hai Hu may publish in the future.
Co-authorship network of co-authors of Hai Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Hai Hu. A scholar is included among the top collaborators of Hai Hu 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 Hai Hu. Hai Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 0 | |
| 11 | 2 | |
| 12 | 5 | |
| 13 | Spatial Metrics of Interaction between CD163-Positive Macrophages and Cancer Cells and Progression-Free Survival in Chemo-Treated Breast Cancer | 15 |
| 14 | 1 | |
| 15 | 9 | |
| 16 | 2 | |
| 17 | 0 | |
| 18 | 184 | |
| 19 | [Multivariate factors analysis on length of stay in Lushan earthquake victims]. | 1 |
| 20 | Efficiency Analysis of Competing Tests for Finding Differentially Expressed Genes in Lung Adenocarcinoma | 1 |
About Hai Hu
Hai Hu is a scholar working on Cancer Research, Oncology and Molecular Biology, having authored 143 papers that have together received 3.0k indexed citations. Recurring topics across this work include Gene expression and cancer classification (13 papers), Cancer-related molecular mechanisms research (12 papers) and RNA modifications and cancer (11 papers). The work is most often cited by research in Cancer Research (791 citations), Molecular Biology (1.8k citations) and Oncology (502 citations). Hai Hu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Frederick Sachs, Craig D. Shriver, Eduardo Marbán, Michael Liebman, Jiao Feng, Cuncun Yuan, Zhen Guo, Ziliang Jin, Xiang Guo and Rick Jordan. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Bioinformatics.
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.