Bai Ji

916 citations
37 papers · 643 · h-index 12

Impact in

  • Biomaterials top 10%
    • Nanoparticle-Based Drug Delivery
  • Hepatology top 10%
    • Hepatocellular Carcinoma Treatment and Prognosis

Papers in

    • Pancreatic and Hepatic Oncology Research 9
    • HER2/EGFR in Cancer Research 3
    • Epigenetics and DNA Methylation 3
    • RNA modifications and cancer 3

Bai Ji

33 papers receiving 635 citations

Peers

Bai Ji
Comparison fields: 5 of 72
  • Biomaterials 155
  • Hepatology 70
  • Cancer Research 89
  • Oncology 149
  • Biomedical Engineering 219
Replace Yufeng Yuan with:
Yufeng Yuan China
Hsi‐Chien Huang Taiwan
Michiel Bolkestein Netherlands
Gilles van Tienderen Netherlands
Dennis Doleschel Germany
Chuandong Zhu China
Donghai Jiang China
Yoshimasa Akashi Japan
Shangzhi Xie China
Yusuke Ohara Japan
Bai Ji relative to Yufeng Yuan China Yufeng Yuan's profile →
Citations per field
00.5×5.7×
Yufeng Yuan · 1×
Citations per year

Countries citing papers authored by Bai Ji

Since Specialization
Citations

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

Fields of papers citing papers by Bai Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bai Ji, 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 Bai Ji Line = papers co-authored together Bai Ji links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202099
2 201778
3 201973
4 202160
5 202159
6 201936
7 201935
8 201934
9 201426
10 201419
11 201417
12 202311
13 202011
14 202410
15 20219
16 20208
17 20218
18 20218
19 20247
20 20245

About Bai Ji

Bai Ji is a scholar working on Oncology, Molecular Biology, Hepatology, Pulmonary and Respiratory Medicine and Cancer Research, having authored 37 papers that have together received 643 indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (9 papers), Hepatocellular Carcinoma Treatment and Prognosis (5 papers), HER2/EGFR in Cancer Research (3 papers), Epigenetics and DNA Methylation (3 papers), RNA modifications and cancer (3 papers), Nanoplatforms for cancer theranostics (3 papers), Ferroptosis and cancer prognosis (2 papers) and Liver Disease Diagnosis and Treatment (2 papers). The work is most often cited by research in Biomaterials (155 citations), Hepatology (70 citations), Cancer Research (89 citations), Oncology (149 citations) and Biomedical Engineering (219 citations). Bai Ji has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Hongqiao Cai, Fei Yan, Yahui Liu, Meiyu Song, Kai Liu, Jianhua Liu, Lingyu Meng, Yang Yang, Songyang Liu and Yahui Liu. Their work appears in journals such as International Journal of Medical Sciences, Oncology Reports, Acta Biomaterialia, Frontiers in Oncology and Archives of Biochemistry and Biophysics.

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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