Sha Lv

535 citations
31 papers · 374 · h-index 10

Impact in

Papers in

    • Cancer-related gene regulation 3
    • Wnt/β-catenin signaling in development and cancer 2
    • Circular RNAs in diseases 2
    • Fungal Infections and Studies 8
    • Nail Diseases and Treatments 3

Sha Lv

29 papers receiving 370 citations

Peers

Sha Lv
Comparison fields: 5 of 90
  • Environmental Engineering 53
  • Civil and Structural Engineering 75
  • Cancer Research 48
  • Building and Construction 27
  • Immunology 41
Replace Zhenxin Wang with:
Zhenxin Wang China
Zhixin Huang China
Jiangang Sun China
Kevin Lamote Belgium
Yao Zhu China
Haiyan Zhang China
Yan‐Nan Liu China
Ryota Inoue Japan
Yifan Liu China
Sha Lv relative to Zhenxin Wang China Zhenxin Wang's profile →
Citations per field
00.5×6.6×
Zhenxin Wang · 1×
Citations per year

Countries citing papers authored by Sha Lv

Since Specialization
Citations

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

Fields of papers citing papers by Sha Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202289
2 201982
3 201431
4 202320
5 202018
6 201918
7 202116
8 201514
9 202210
10 20219
11 20147
12 20157
13 20147
14 20166
15 20235
16 20245
17 20214
18 20244
19 20253
20 20123

About Sha Lv

Sha Lv is a scholar working on Molecular Biology, Epidemiology, Cell Biology, Immunology and Cancer Research, having authored 31 papers that have together received 374 indexed citations. Recurring topics across this work include Fungal Infections and Studies (8 papers), Plant Pathogens and Fungal Diseases (3 papers), Cancer-related gene regulation (3 papers), Nail Diseases and Treatments (3 papers), Infectious Diseases and Mycology (3 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers), Wnt/β-catenin signaling in development and cancer (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Environmental Engineering (53 citations), Civil and Structural Engineering (75 citations), Cancer Research (48 citations), Building and Construction (27 citations) and Immunology (41 citations). Sha Lv has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Fuqiu Li, Fen‐Fang Hong, Shu‐Long Yang, Wei Liu, Xiaoyu Liang, Haibin Kuang, Tao Li, Chentao Zhang, Bin Li and Haoyang Sun. Their work appears in journals such as Scientific Reports, BMC Infectious Diseases, Inflammation Research, Mycopathologia and Infection and Drug Resistance.

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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