Yang Lv

957 citations
46 papers · 568 · h-index 15

Impact in

Papers in

    • Microbial Metabolic Engineering and Bioproduction 5
    • RNA Interference and Gene Delivery 3
    • Microbial metabolism and enzyme function 3
    • Reproductive System and Pregnancy 4

Yang Lv

42 papers receiving 558 citations

Peers

Yang Lv
Comparison fields: 5 of 105
  • Cancer Research 63
  • Obstetrics and Gynecology 30
  • Molecular Biology 290
  • Immunology 62
  • Genetics 30
Replace Padma-Sheela Jayaraman with:
Padma-Sheela Jayaraman United Kingdom
Sanhita Ray United States
Johann Urschitz United States
Yingli Han China
Mei‐Chun Lin Taiwan
Guoxing Zhu China
Carol S. Auletta United States
Gie‐Taek Chun South Korea
Yang Lv relative to Padma-Sheela Jayaraman United Kingdom Padma-Sheela Jayaraman's profile →
Citations per field
00.5×2.7×
Padma-Sheela Jayaraman · 1×
Citations per year

Countries citing papers authored by Yang Lv

Since Specialization
Citations

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

Fields of papers citing papers by Yang Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201562
2 201554
3 202042
4 200836
5 201529
6 201528
7 201327
8 201625
9 201924
10 202421
11 201119
12 201117
13 202217
14 201315
15 202215
16 201014
17 200811
18 201911
19 202111
20 201410

About Yang Lv

Yang Lv is a scholar working on Molecular Biology, Immunology, Surgery, Physiology and Cancer Research, having authored 46 papers that have together received 568 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers), Reproductive System and Pregnancy (4 papers), Adipose Tissue and Metabolism (4 papers), Lipid metabolism and biosynthesis (4 papers), Biofuel production and bioconversion (4 papers), RNA Interference and Gene Delivery (3 papers) and Microbial metabolism and enzyme function (3 papers). The work is most often cited by research in Cancer Research (63 citations), Obstetrics and Gynecology (30 citations), Molecular Biology (290 citations), Immunology (62 citations) and Genetics (30 citations). Yang Lv has collaborated with scholars based in China, United Kingdom and Germany. Frequent co-authors include Guangpeng Li, Zhuying Wei, Dabing Zhang, Zoran Nikoloski, Xiujuan Chen, Xuetao Pei, David Twell, Lei Yang, Yongchun Zuo and Guo-Liang Fan. Their work appears in journals such as PLoS ONE, Gene, Fertility and Sterility, Current Issues in Molecular Biology and Biofuels Bioproducts and Biorefining.

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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