Tu Lu

873 citations
7 papers · 577 · h-index 6

Impact in

  • Aging top 1%
    • Genetics, Aging, and Longevity in Model Organisms
    • RNA Research and Splicing
    • CRISPR and Genetic Engineering
    • RNA modifications and cancer
    • RNA and protein synthesis mechanisms
    • Genomics and Chromatin Dynamics
    • Nuclear Structure and Function
    • Fungal and yeast genetics research

Papers in

    • RNA modifications and cancer 2
    • CRISPR and Genetic Engineering 2
    • RNA Research and Splicing 2
    • RNA and protein synthesis mechanisms 1
    • Genetics, Aging, and Longevity in Model Organisms 3

Tu Lu

7 papers receiving 567 citations

Peers

Tu Lu
Comparison fields: 5 of 56
  • Aging 212
  • Molecular Biology 503
  • Business and International Management 12
  • Cell Biology 80
  • Endocrine and Autonomic Systems 19
Replace Deepika Calidas with:
Deepika Calidas United States
Chih-Yung S. Lee United States
Yihong Yang China
Vincent Portegijs Netherlands
Alexey V. Pindyurin Russia
Christian A Grove United States
Joshua N. Bembenek United States
Sandro Baldi Germany
Tory Herman United States
Ofer Rog United States
Tu Lu relative to Deepika Calidas United States Deepika Calidas's profile →
Citations per field
00.5×1.5×
Deepika Calidas · 1×
Citations per year

Countries citing papers authored by Tu Lu

Since Specialization
Citations

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

Fields of papers citing papers by Tu Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 2014218
2 2016172
3 202086
4 201143
5 201737
6 201119
7 20232

About Tu Lu

Tu Lu is a scholar working on Molecular Biology, Aging, Cell Biology, Ophthalmology and Physiology, having authored 7 papers that have together received 577 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (3 papers), RNA modifications and cancer (2 papers), CRISPR and Genetic Engineering (2 papers), RNA Research and Splicing (2 papers), Cellular transport and secretion (2 papers), RNA and protein synthesis mechanisms (1 paper), Lysosomal Storage Disorders Research (1 paper) and Retinal Diseases and Treatments (1 paper). The work is most often cited by research in Aging (212 citations), Molecular Biology (503 citations), Business and International Management (12 citations), Cell Biology (80 citations) and Endocrine and Autonomic Systems (19 citations). Tu Lu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Géraldine Seydoux, Deepika Calidas, Helen Schmidt, Jarrett Smith, Chih-Yung S. Lee, Dominique Rasoloson, Michael Krause, Alexandre Paix, Yuemeng Wang and Harold E. Smith. Their work appears in journals such as eLife, Photodiagnosis and Photodynamic Therapy, Molecular Biology of the Cell, Genetics and Lab on a Chip.

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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