Haibo Han

1.4k citations
42 papers · 1.0k indexed · h-index 17

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Cancer, Hypoxia, and Metabolism
    • Circular RNAs in diseases
    • RNA modifications and cancer
    • Epigenetics and DNA Methylation
    • RNA Research and Splicing

Papers in

Haibo Han

41 papers receiving 1.0k citations

Peers

Haibo Han
Comparison fields: 5 of 87
  • Cancer Research 510
  • Molecular Biology 735
  • Oncology 262
  • Cell Biology 75
  • Hepatology 32
Replace Yiji Liao with:
Yiji Liao China
Huahong Xie China
Zhi‐Zhou Shi China
Shuang Han China
Jia‐Jie Hao China
Shih Hwa Chiou Taiwan
Shu Shimada Japan
Jiang Yin China
Dacheng Xie China
Kathleen E. DelGiorno United States
Haibo Han relative to Yiji Liao China Yiji Liao's profile →
Citations per field
00.5×1.5×
Yiji Liao · 1×
Citations per year

Countries citing papers authored by Haibo Han

Since Specialization
Citations

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

Fields of papers citing papers by Haibo Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Haibo Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Haibo Han Line = papers co-authored together Haibo Han links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202311
2 202314
3 20230
4 20236
5 20237
6 202128
7 20218
8 202110
9 202126
10 202027
11 202030
12
The combination of circRNA-UMAD1 and Galectin-3 in peripheral circulation is a co-biomarker for predicting lymph node metastasis of thyroid carcinoma.
202011
13 201937
14 201812
15 201810
16 20179
17 201720
18 201563
19 2013133
20 2013165

About Haibo Han

Haibo Han is a scholar working on Cancer Research, Cell Biology, Oncology, Molecular Biology and Immunology, having authored 42 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (13 papers), MicroRNA in disease regulation (8 papers), RNA modifications and cancer (8 papers), Cancer Cells and Metastasis (7 papers), Circular RNAs in diseases (7 papers), Epigenetics and DNA Methylation (5 papers), RNA Research and Splicing (4 papers) and Ferroptosis and cancer prognosis (3 papers). The work is most often cited by research in Cancer Research (510 citations), Molecular Biology (735 citations), Oncology (262 citations), Cell Biology (75 citations) and Hepatology (32 citations). Haibo Han has collaborated with scholars based in China, Ethiopia and United States. Frequent co-authors include Zhiqian Zhang, Wei Zhao, Jinfeng Chen, Yuanyuan Ma, Yue Yang, Jianzhi Zhang, Baocai Xing, Jiafu Ji, Ting Guo and Fang Fang. Their work appears in journals such as Oncotarget, Cell Death and Disease, Cell Death Discovery, Nature Communications and Cancer Communications.

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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