Sha Yang

809 citations
30 papers · 609 · h-index 13

Impact in

    • MicroRNA in disease regulation
    • Advanced biosensing and bioanalysis techniques
    • RNA Interference and Gene Delivery
    • Extracellular vesicles in disease
    • DNA and Nucleic Acid Chemistry

Papers in

    • Advanced biosensing and bioanalysis techniques 16
    • RNA Interference and Gene Delivery 13
    • Extracellular vesicles in disease 3
    • Biosensors and Analytical Detection 4

Sha Yang

28 papers receiving 598 citations

Peers

Sha Yang
Comparison fields: 5 of 89
  • Cancer Research 97
  • Molecular Biology 416
  • Hepatology 45
  • Biomedical Engineering 214
  • Electrochemistry 20
Replace Shi‐Yan Zhang with:
Shi‐Yan Zhang China
Timothy K. Toby United States
Andrew T. Sage Canada
Hong-Yi Xie China
Xiumei Wu China
Sang Wook Oh South Korea
Yi Mao China
Yongmei Tian China
Martin Bunček Czechia
Qingxiang Zhang China
Sha Yang relative to Shi‐Yan Zhang China Shi‐Yan Zhang's profile →
Citations per field
00.5×10.7×
Shi‐Yan Zhang · 1×
Citations per year

Countries citing papers authored by Sha Yang

Since Specialization
Citations

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

Fields of papers citing papers by Sha Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201885
2 202178
3 202170
4 202055
5 202338
6 202337
7 201834
8 201630
9 201625
10 202020
11 202319
12 202219
13 202414
14 202311
15 202111
16 20239
17 20218
18 20238
19 20238
20 20207

About Sha Yang

Sha Yang is a scholar working on Molecular Biology, Biomedical Engineering, Cancer Research, Infectious Diseases and Electrical and Electronic Engineering, having authored 30 papers that have together received 609 indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (16 papers), RNA Interference and Gene Delivery (13 papers), MicroRNA in disease regulation (6 papers), Biosensors and Analytical Detection (4 papers), Extracellular vesicles in disease (3 papers), Terahertz technology and applications (2 papers), Drug-Induced Hepatotoxicity and Protection (2 papers) and Liver Disease and Transplantation (2 papers). The work is most often cited by research in Cancer Research (97 citations), Molecular Biology (416 citations), Hepatology (45 citations), Biomedical Engineering (214 citations) and Electrochemistry (20 citations). Sha Yang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ming Chen, Kai Chang, Xiaoqi Tang, Lianyu Yu, Shuang Zhao, Wenqing Zhang, Weiling Fu, Xinyu Zhan, Yang Xiang and Lin Zhou. Their work appears in journals such as Biosensors and Bioelectronics, Analytica Chimica Acta, Advanced Science, Energies and Advanced Materials Technologies.

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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