Chin-Chun Lu

3.2k citations
12 papers · 1.6k · h-index 11

Impact in

Papers in

    • Protein Degradation and Inhibitors 7
    • Ubiquitin and proteasome pathways 5
    • Histone Deacetylase Inhibitors Research 3
    • Wnt/β-catenin signaling in development and cancer 2
    • Axon Guidance and Neuronal Signaling 4
    • Nerve injury and regeneration 4

Chin-Chun Lu

12 papers receiving 1.6k citations

Peers

Chin-Chun Lu
Comparison fields: 5 of 79
  • Developmental Neuroscience 326
  • Cellular and Molecular Neuroscience 814
  • Aging 55
  • Hematology 175
  • Cell Biology 254
Replace Raja Kittappa with:
Raja Kittappa United States
Raffaella Scardigli Italy
Michael M. Halford Australia
Renate Lewis United States
Luis García‐Alonso Spain
Laura Wagstaff United Kingdom
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Kit Wong United States
Darcie L. Moore United States
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Citations per field
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Citations per year

Countries citing papers authored by Chin-Chun Lu

Since Specialization
Citations

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

Fields of papers citing papers by Chin-Chun Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chin-Chun Lu. 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 Chin-Chun Lu. The network helps show where Chin-Chun Lu may publish in the future.

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2003469
2 2005243
3 2005226
4 2017212
5 2008144
6 201676
7 201769
8 201765
9 201856
10 201919
11 201916
12 20197

About Chin-Chun Lu

Chin-Chun Lu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Hematology, Cell Biology and Developmental Neuroscience, having authored 12 papers that have together received 1.6k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (7 papers), Ubiquitin and proteasome pathways (5 papers), Axon Guidance and Neuronal Signaling (4 papers), Nerve injury and regeneration (4 papers), Multiple Myeloma Research and Treatments (4 papers), Histone Deacetylase Inhibitors Research (3 papers), Neurogenesis and neuroplasticity mechanisms (2 papers) and Wnt/β-catenin signaling in development and cancer (2 papers). The work is most often cited by research in Developmental Neuroscience (326 citations), Cellular and Molecular Neuroscience (814 citations), Aging (55 citations), Hematology (175 citations) and Cell Biology (254 citations). Chin-Chun Lu has collaborated with scholars based in United States and Russia. Frequent co-authors include Yimin Zou, Leslie A. King, Anna I Lyuksyutova, Jun Shi, Marc Tessier‐Lavigne, Nini Guo, Yanshu Wang, Jeremy Nathans, Adam M. Schmitt and Gang Lu. Their work appears in journals such as Blood, Journal of Medicinal Chemistry, Nature Neuroscience, Nature and Proceedings of the National Academy of 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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