William B. Tu

1.2k citations
14 papers · 760 · h-index 9

Impact in

    • Protein Degradation and Inhibitors
    • Ubiquitin and proteasome pathways
    • Genomics and Chromatin Dynamics
    • Epigenetics and DNA Methylation
    • Cancer-related gene regulation
    • RNA modifications and cancer
    • Histone Deacetylase Inhibitors Research

Papers in

    • Ubiquitin and proteasome pathways 6
    • Protein Degradation and Inhibitors 4
    • Genomics and Chromatin Dynamics 4
    • Angiogenesis and VEGF in Cancer 1
    • DNA Repair Mechanisms 1
    • Cancer-related Molecular Pathways 2

William B. Tu

14 papers receiving 754 citations

Peers

William B. Tu
Comparison fields: 5 of 76
  • Molecular Biology 585
  • Cancer Research 96
  • Oncology 164
  • Cell Biology 93
  • Aging 7
Replace Marian M. Deuker with:
Marian M. Deuker United States
Shankar Varadarajan United Kingdom
Víctor J. Sánchez‐Arévalo Lobo Spain
Yeonjoo Jung South Korea
Dana S. Neel United States
Cindy Wilson United States
Ricarda Herr Germany
Z. Ping Lin United States
Jagruti Patel United States
William B. Tu relative to Marian M. Deuker United States Marian M. Deuker's profile →
Citations per field
00.5×1.5×1.9×
Marian M. Deuker · 1×
Citations per year

Countries citing papers authored by William B. Tu

Since Specialization
Citations

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

Fields of papers citing papers by William B. Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 2017293
2 201497
3 201491
4 201890
5 201846
6 201642
7 201730
8 201325
9 201622
10 20258
11 20238
12 20164
13 20133
14 20251

About William B. Tu

William B. Tu is a scholar working on Molecular Biology, Oncology, Cell Biology, Physiology and Cancer Research, having authored 14 papers that have together received 760 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (6 papers), Protein Degradation and Inhibitors (4 papers), Genomics and Chromatin Dynamics (4 papers), Cancer-related Molecular Pathways (2 papers), Adipose Tissue and Metabolism (2 papers), Cancer Mechanisms and Therapy (1 paper), Angiogenesis and VEGF in Cancer (1 paper) and DNA Repair Mechanisms (1 paper). The work is most often cited by research in Molecular Biology (585 citations), Cancer Research (96 citations), Oncology (164 citations), Cell Biology (93 citations) and Aging (7 citations). William B. Tu has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Linda Z. Penn, Corey Lourenco, Manpreet Kalkat, Jason De Melo, Diana Resetca, Brian Raught, Igor Jurišica, Dharmendra Dingar, Paul C. Boutros and Pak-Kei Chan. Their work appears in journals such as Nature Communications, Oncogene, Cell Cycle, Genome biology and Cell.

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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