Z. Zu

794 citations
6 papers · 512 indexed · h-index 5

Impact in

  • Hematology top 5%
    • Hematopoietic Stem Cell Transplantation
    • Chronic Myeloid Leukemia Treatments
    • Acute Myeloid Leukemia Research
  • Genetics top 10%
    • Virus-based gene therapy research
    • Chronic Lymphocytic Leukemia Research

Papers in

Z. Zu

5 papers receiving 483 citations

Peers

Z. Zu
Comparison fields: 5 of 50
  • Hematology 239
  • Genetics 96
  • Oncology 186
  • Genetics 177
  • Immunology 74
Replace DA Williams with:
DA Williams United States
CL Reading United States
HP Kiem United States
S Cayeux Germany
Mattias Magnusson Sweden
Richard Howrey United States
S Kyoizumi United States
Ursula R. Sorg Germany
F Schuening United States
Rodolphe Vereecque France
Z. Zu relative to DA Williams United States DA Williams's profile →
Citations per field
00.5×
DA Williams · 1×
Citations per year

Countries citing papers authored by Z. Zu

Since Specialization
Citations

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

Fields of papers citing papers by Z. Zu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 22 scholars most cited alongside Z. Zu, 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 Z. Zu Line = papers co-authored together Z. Zu links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1 20246
2 20110
3
Resistance to taxol chemotherapy produced in mouse marrow cells by safety-modified retroviruses containing a human MDR-1 transcription unit.
199565
4
Chemotherapy resistance to taxol in clonogenic progenitor cells following transduction of CD34 selected marrow and peripheral blood cells with a retrovirus that contains the MDR-1 chemotherapy resistance gene.
199533
5
PML/RARalpha, a fusion protein in acute promyelocytic leukemia, prevents growth factor withdrawal-induced apoptosis in TF-1 cells.
199514
6 1994394

About Z. Zu

Z. Zu is a scholar working on Hematology, Cancer Research, Complementary and alternative medicine, Reproductive Medicine and Genetics, having authored 6 papers that have together received 512 indexed citations. Recurring topics across this work include Cancer therapeutics and mechanisms (1 paper), Acute Myeloid Leukemia Research (1 paper), interferon and immune responses (1 paper), DNA Repair Mechanisms (1 paper), Chronic Lymphocytic Leukemia Research (1 paper), Sleep and related disorders (1 paper), Retinoids in leukemia and cellular processes (1 paper) and Cancer, Lipids, and Metabolism (1 paper). The work is most often cited by research in Hematology (239 citations), Genetics (96 citations), Oncology (186 citations), Genetics (177 citations) and Immunology (74 citations). Z. Zu has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Siqing Fu, David F. Claxton, Michael W. Thomas, WF Anderson, Debra Ellerson, Laura Goldberg, Elie G. Hanania, A. B. Deisseroth, Igor B. Roninson and Michael Andreeff. Their work appears in journals such as Journal of Clinical Oncology, Complementary Therapies in Medicine, Blood and PubMed.

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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2026