Yu Liang

5.3k total citations · 3 hit papers
29 papers, 4.3k citations indexed

About

Yu Liang is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Yu Liang has authored 29 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 21 papers in Cancer Research and 3 papers in Genetics. Recurrent topics in Yu Liang's work include Cancer-related molecular mechanisms research (16 papers), MicroRNA in disease regulation (15 papers) and Circular RNAs in diseases (14 papers). Yu Liang is often cited by papers focused on Cancer-related molecular mechanisms research (16 papers), MicroRNA in disease regulation (15 papers) and Circular RNAs in diseases (14 papers). Yu Liang collaborates with scholars based in China, United States and Norway. Yu Liang's co-authors include Caifu Chen, Dana Ridzon, Linda Wong, Wen Xue, Michele A. Cleary, Zhenyu Xuan, Lin He, Aimee L. Jackson, Xingyue He and Lee P. Lim and has published in prestigious journals such as Nature, Cancer Research and Plant Cell & Environment.

In The Last Decade

Yu Liang

28 papers receiving 4.3k citations

Hit Papers

A microRNA component of the p53 tumour suppressor network 2007 2026 2013 2019 2007 2007 2007 500 1000 1.5k 2.0k

Peers

Yu Liang
Comparison fields: 5 of 124
  • Molecular Biology 3.5k
  • Cancer Research 3.4k
  • Oncology 342
  • Immunology 227
  • Pulmonary and Respiratory Medicine 152
Replace Jia Yu with:
Jia Yu China
Dana Ridzon United States
Xiaowei Wang China
Susanna Obad United States
Richard I. Gregory United States
Stefan J. Erkeland Netherlands
Je‐Hyun Yoon United States
Shu‐Chun Lin Taiwan
Ayelet Chajut United States
Kevin Kelnar United States
Jia Yu China View profile →
Citations per field, relative to Yu Liang
Yu Liang · 1×
Citations per year, relative to Yu Liang
Yu Liang · 1×

Countries citing papers authored by Yu Liang

Since Specialization
Citations

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

Fields of papers citing papers by Yu Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Liang. A scholar is included among the top collaborators of Yu Liang 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 Yu Liang. Yu Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 6
4 15
5 11
6 5
7 5
8 3
9 252
10 22
11 1
12 23
13 13
14 1
15 42
16 12
17 43
18
Characterization of MicroRNA Expression Levels and Their Biological Correlates in Human Cancer Cell Lines breakdown →
586
19
A microRNA component of the p53 tumour suppressor network breakdown →
2177
20
Intravesical immunotoxin as adjuvant therapy to prevent the recurrence of bladder cancer.
8

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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