Xiaoling Lv

646 citations
35 papers · 458 · h-index 13

Impact in

Papers in

Xiaoling Lv

32 papers receiving 453 citations

Peers

Xiaoling Lv
Comparison fields: 5 of 90
  • Animal Science and Zoology 55
  • Small Animals 24
  • Health Informatics 4
  • Orthopedics and Sports Medicine 21
  • Biological Psychiatry 6
Replace Thiago Pinheiro Arrais Aloia with:
Thiago Pinheiro Arrais Aloia Brazil
Teresa Bruna Pagano Italy
Karolina A. P. Wijnands Netherlands
Semone B. Myrie Canada
Anita Nishiyama Brazil
Marina Facci Canada
Xiaoli Zhou China
Seppo Hyyppä Finland
Jason Lei United States
Xiaoling Lv relative to Thiago Pinheiro Arrais Aloia Brazil Thiago Pinheiro Arrais Aloia's profile →
Citations per field
00.5×5.3×
Thiago Pinheiro Arrais Aloia · 1×
Citations per year

Countries citing papers authored by Xiaoling Lv

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoling Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201452
2 202045
3 201543
4 201438
5 201832
6 201126
7 202225
8 201719
9 202119
10 202019
11 202318
12 201716
13 201114
14 202111
15 202311
16 20239
17 20229
18 20239
19 20206
20 20236

About Xiaoling Lv

Xiaoling Lv is a scholar working on Animal Science and Zoology, Parasitology, Small Animals, Molecular Biology and Cancer Research, having authored 35 papers that have together received 458 indexed citations. Recurring topics across this work include Coccidia and coccidiosis research (13 papers), Parasitic Infections and Diagnostics (9 papers), Veterinary medicine and infectious diseases (7 papers), Animal Nutrition and Physiology (3 papers), Bone Metabolism and Diseases (3 papers), Circular RNAs in diseases (2 papers), Bone health and osteoporosis research (2 papers) and Food composition and properties (2 papers). The work is most often cited by research in Animal Science and Zoology (55 citations), Small Animals (24 citations), Health Informatics (4 citations), Orthopedics and Sports Medicine (21 citations) and Biological Psychiatry (6 citations). Xiaoling Lv has collaborated with scholars based in China and United States. Frequent co-authors include Genxiang Mao, Wenyan Gao, Wenmin Xing, Zhongshan Zhang, Weihong Xu, Guofu Wang, Guihua Wang, Yazhen Wang, Qing Wu and Qian Zhang. Their work appears in journals such as Poultry Science, Animals, Artificial Intelligence in Medicine, Medicine and Neurological Sciences.

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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