Xiaodan Lv

4.4k citations
42 papers · 1.5k · 1 hit paper · h-index 15

Impact in

    • Genomics and Chromatin Dynamics
    • RNA Research and Splicing
    • Epigenetics and DNA Methylation
    • RNA and protein synthesis mechanisms
    • RNA modifications and cancer
    • Single-cell and spatial transcriptomics

Papers in

Xiaodan Lv

41 papers receiving 1.5k citations

Xiaodan Lv's Hit Papers

Multiscale 3D Genome Rewiring during Mouse Neural Development 2017 · 821 citations
8210+3+6Years since publication250500750

Peers

Xiaodan Lv
Comparison fields: 5 of 114
  • Obstetrics and Gynecology 137
  • Molecular Biology 1.0k
  • Cancer Research 134
  • Reproductive Medicine 70
  • Immunology 175
Replace Hong Lv with:
Hong Lv China
Jing Bian China
Jian Zhao China
Jiajie Tu China
Carlton L. Schwab United States
Jizong Lin China
Xiaodan Lv relative to Hong Lv China Hong Lv's profile →
Citations per field
00.5×4.5×
Hong Lv · 1×
Citations per year

Countries citing papers authored by Xiaodan Lv

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodan Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Multiscale 3D Genome Rewiring during Mouse Neural Development
Hit paper breakdown →
2017821
2 2018154
3 201454
4 202049
5 201647
6 202233
7 201632
8 202329
9 202128
10 201728
11 201725
12 201621
13 201821
14 202118
15 201616
16 202113
17 202013
18 202012
19 201710
20 20249

About Xiaodan Lv

Xiaodan Lv is a scholar working on Molecular Biology, Immunology, Genetics, Epidemiology and Plant Science, having authored 42 papers that have together received 1.5k indexed citations. Recurring topics across this work include Inflammatory Bowel Disease (5 papers), Gynecological conditions and treatments (4 papers), Reproductive System and Pregnancy (4 papers), Liver Disease Diagnosis and Treatment (3 papers), IL-33, ST2, and ILC Pathways (3 papers), Mesenchymal stem cell research (2 papers), Allergic Rhinitis and Sensitization (2 papers) and Galectins and Cancer Biology (2 papers). The work is most often cited by research in Obstetrics and Gynecology (137 citations), Molecular Biology (1.0k citations), Cancer Research (134 citations), Reproductive Medicine (70 citations) and Immunology (175 citations). Xiaodan Lv has collaborated with scholars based in China, United Kingdom and Israel. Frequent co-authors include Lauriane Fritsch, Xiaole Xu, Giacomo Cavalli, Giorgio L. Papadopoulos, Jean‐Philippe Hugnot, Amos Tanay, Quentin Szabo, Netta Mendelson Cohen, Yaniv Lubling and Boyan Bonev. Their work appears in journals such as Scientific Reports, Oncotarget, Gut Microbes, Reproductive BioMedicine Online and Frontiers in Pharmacology.

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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