Gan Yang

418 citations
16 papers · 300 · h-index 7

Impact in

Papers in

    • Aquaculture Nutrition and Growth 5
    • Genetic and phenotypic traits in livestock 2
    • Connective tissue disorders research 1

Gan Yang

14 papers receiving 290 citations

Peers

Gan Yang
Comparison fields: 5 of 68
  • Energy Engineering and Power Technology 44
  • Aquatic Science 32
  • Building and Construction 42
  • Mechanical Engineering 115
  • Renewable Energy, Sustainability and the Environment 48
Replace Ma. Dolores Durán-García with:
Ma. Dolores Durán-García Mexico
Sara Baddadi Tunisia
Giancarlo Marafioti Norway
Kazem Shahverdi Iran
Said Saadeddine Morocco
D. G. Colliver United States
Safa Skouri Tunisia
Francesco Tariello Italy
R. Kamaruddin Malaysia
Andrés J. Díaz Chile
Gan Yang relative to Ma. Dolores Durán-García Mexico Ma. Dolores Durán-García's profile →
Citations per field
00.5×
Ma. Dolores Durán-García · 1×
Citations per year

Countries citing papers authored by Gan Yang

Since Specialization
Citations

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

Fields of papers citing papers by Gan Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2018168
2 200355
3 202219
4 202212
5 202211
6 20248
7 20217
8 20204
9 20193
10 20233
11 20183
12 20212
13 20252
14 20232
15 20231
16 20240

About Gan Yang

Gan Yang is a scholar working on Aquatic Science, Genetics, Surgery, Cardiology and Cardiovascular Medicine and Physiology, having authored 16 papers that have together received 300 indexed citations. Recurring topics across this work include Aquaculture Nutrition and Growth (5 papers), Genetic and phenotypic traits in livestock (2 papers), Reproductive biology and impacts on aquatic species (2 papers), Marine Bivalve and Aquaculture Studies (2 papers), Connective tissue disorders research (1 paper), COVID-19 diagnosis using AI (1 paper), Marine and fisheries research (1 paper) and Neonatal and fetal brain pathology (1 paper). The work is most often cited by research in Energy Engineering and Power Technology (44 citations), Aquatic Science (32 citations), Building and Construction (42 citations), Mechanical Engineering (115 citations) and Renewable Energy, Sustainability and the Environment (48 citations). Gan Yang has collaborated with scholars based in China and United States. Frequent co-authors include Xiaoqiang Zhai, Liang‐Shih Fan, Weiwei You, Caihuan Ke, Xuan Luo, Yawei Shen, Qizhen Xiao, Yi Wang, Jianpeng Zhang and Zekun Huang. Their work appears in journals such as Aquaculture, Aquaculture Reports, Annals of Palliative Medicine, International Journal of Cardiology and Sensors.

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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