Linya Wang

747 citations
22 papers · 540 · h-index 9

Impact in

  • Hepatology top 10%
    • Hepatitis C virus research
  • Epidemiology top 10%
    • Autophagy in Disease and Therapy
    • Liver Disease Diagnosis and Treatment

Papers in

Linya Wang

21 papers receiving 539 citations

Peers

Linya Wang
Comparison fields: 5 of 72
  • Hepatology 77
  • Epidemiology 331
  • Physiology 31
  • Cancer Research 102
  • Cell Biology 93
Replace Mengdie Fang with:
Mengdie Fang China
Liang Da China
Yasutoshi Nozaki Japan
Guozhong Gong China
Chunhong Feng China
Michal Kandel-Kfir Israel
Chaewon Lee Hong Kong
Ruichao Yue China
Linya Wang relative to Mengdie Fang China Mengdie Fang's profile →
Citations per field
00.5×2.5×
Mengdie Fang · 1×
Citations per year

Countries citing papers authored by Linya Wang

Since Specialization
Citations

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

Fields of papers citing papers by Linya Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017204
2 2015104
3 201752
4 201550
5 201723
6 202218
7 201817
8 202311
9 20248
10 20247
11 20246
12 20246
13 20216
14 20196
15 20156
16 20244
17 20254
18 20224
19 20232
20 20251

About Linya Wang

Linya Wang is a scholar working on Molecular Biology, Epidemiology, Hepatology, Pulmonary and Respiratory Medicine and Cell Biology, having authored 22 papers that have together received 540 indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (8 papers), Retinoids in leukemia and cellular processes (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Ferroptosis and cancer prognosis (3 papers), Hepatitis C virus research (3 papers), Cancer, Lipids, and Metabolism (2 papers), Acute Myeloid Leukemia Research (2 papers) and Acute Lymphoblastic Leukemia research (2 papers). The work is most often cited by research in Hepatology (77 citations), Epidemiology (331 citations), Physiology (31 citations), Cancer Research (102 citations) and Cell Biology (93 citations). Linya Wang has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Jing‐hsiung James Ou, Yongjun Tian, Ji‐Young Lee, Stephanie T. Chan, Dexi Chen, Keigo Machida, Kai Liu, Helene Minyi Liu, Michael M. C. Lai and Huyong Zheng. Their work appears in journals such as PLoS Pathogens, Forests, Pharmacogenomics, Biological Chemistry and Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids.

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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