Mingming Lv

1.4k citations
56 papers · 1.0k · h-index 19

Impact in

Papers in

    • RNA modifications and cancer 7
    • Circular RNAs in diseases 6
    • Cancer-related molecular mechanisms research 13
    • MicroRNA in disease regulation 4

Mingming Lv

54 papers receiving 1.0k citations

Peers

Mingming Lv
Comparison fields: 5 of 87
  • Cancer Research 457
  • Obstetrics and Gynecology 60
  • Molecular Biology 443
  • Oncology 149
  • Genetics 56
Replace Valeria Zuccalà with:
Valeria Zuccalà Italy
Shinji Iizuka Japan
Geunghwan Ahn South Korea
Gyeong Sin Park South Korea
Chiara Gai Italy
Pingli Xie China
Fethi Guémira Tunisia
Tse-Ching Chen Taiwan
Laia Fina United Kingdom
Sarah Duff United Kingdom
Mingming Lv relative to Valeria Zuccalà Italy Valeria Zuccalà's profile →
Citations per field
00.5×1.5×
Valeria Zuccalà · 1×
Citations per year

Countries citing papers authored by Mingming Lv

Since Specialization
Citations

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

Fields of papers citing papers by Mingming Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014100
2 201682
3 201566
4 201664
5 201558
6 201957
7 201247
8 201137
9 201434
10 201030
11 202030
12 201929
13 201728
14 201226
15 201526
16 202324
17 202023
18 201621
19 201919
20 201416

About Mingming Lv

Mingming Lv is a scholar working on Molecular Biology, Cancer Research, Surgery, Oncology and Otorhinolaryngology, having authored 56 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (13 papers), RNA modifications and cancer (7 papers), Circular RNAs in diseases (6 papers), Head and Neck Cancer Studies (5 papers), Bone Tumor Diagnosis and Treatments (4 papers), Pregnancy and preeclampsia studies (4 papers), Mycobacterium research and diagnosis (4 papers) and MicroRNA in disease regulation (4 papers). The work is most often cited by research in Cancer Research (457 citations), Obstetrics and Gynecology (60 citations), Molecular Biology (443 citations), Oncology (149 citations) and Genetics (56 citations). Mingming Lv has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Yayi Hou, Cheng Lu, Tingting Wang, Xun Lu, Sunan Shen, Yujun Xu, Fengliang Wang, Pengfei Xu, Ruijing Tang and Jing Ren. Their work appears in journals such as Biomedicine & Pharmacotherapy, CardioVascular and Interventional Radiology, Frontiers in Oncology, Oral Oncology and Frontiers in Genetics.

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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