Liyu Wu

533 citations
8 papers · 452 · h-index 6

Impact in

    • TGF-β signaling in diseases
    • Ubiquitin and proteasome pathways
    • Cancer-related gene regulation
    • Metabolism, Diabetes, and Cancer
    • Bone Metabolism and Diseases

Papers in

    • TGF-β signaling in diseases 5
    • Bone Metabolism and Diseases 2
    • Protein Kinase Regulation and GTPase Signaling 2
    • Metabolism, Diabetes, and Cancer 2
    • Protease and Inhibitor Mechanisms 1

Liyu Wu

7 papers receiving 446 citations

Peers

Liyu Wu
Comparison fields: 5 of 58
  • Cancer Research 72
  • Molecular Biology 335
  • Oncology 109
  • Immunology and Allergy 15
  • Genetics 54
Replace Toshihide Nishishita with:
Toshihide Nishishita Japan
Sporn Mb United States
Minnkyong Lee United States
Zexuan Liu China
Daniel R. Radiloff United States
Maria Alfonso-Jaume United States
Michael WY Chan Taiwan
Ana Rita Lourenço Netherlands
Céline Chipoy France
Eun Suk Hwang South Korea
Liyu Wu relative to Toshihide Nishishita Japan Toshihide Nishishita's profile →
Citations per field
00.5×
Toshihide Nishishita · 1×
Citations per year

Countries citing papers authored by Liyu Wu

Since Specialization
Citations

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

Fields of papers citing papers by Liyu Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Liyu Wu, 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 Liyu Wu Line = papers co-authored together Liyu Wu links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2009145
2 2002141
3 200384
4 200533
5 200930
6 200518
7
Effect of Hormonal Drugs on Normal SD Rat Hypothalamus-Pituitary-Adrenal Axis Based on H-E Staining and Immunohistochemical Technique
20151
8
The Application of Excel in the Students' Transcripts Schedule
20110

About Liyu Wu

Liyu Wu is a scholar working on Molecular Biology, Cancer Research, Pathology and Forensic Medicine, Information Systems and Oncology, having authored 8 papers that have together received 452 indexed citations. Recurring topics across this work include TGF-β signaling in diseases (5 papers), Bone Metabolism and Diseases (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Cancer-related Molecular Pathways (1 paper), Estrogen and related hormone effects (1 paper), Protease and Inhibitor Mechanisms (1 paper) and Genetic factors in colorectal cancer (1 paper). The work is most often cited by research in Cancer Research (72 citations), Molecular Biology (335 citations), Oncology (109 citations), Immunology and Allergy (15 citations) and Genetics (54 citations). Liyu Wu has collaborated with scholars based in United States and China. Frequent co-authors include Rik Derynck, Xu Cao, Mei Wan, Yalei Wu, Ning Wang, Xingming Shi, Shuting Bai, Xuesong Cao, William E. Grizzle and Xuelin Li. Their work appears in journals such as Journal of Biological Chemistry, Developmental Cell, Breast Cancer Research and Treatment, Molecular Cancer and EMBO Reports.

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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