Gary Lu

2.2k citations
69 papers · 1.4k · h-index 21

Impact in

Papers in

    • Acute Myeloid Leukemia Research 24
    • Chronic Myeloid Leukemia Treatments 14
    • Multiple Myeloma Research and Treatments 8
    • Chronic Lymphocytic Leukemia Research 11
    • Myeloproliferative Neoplasms: Diagnosis and Treatment 6

Gary Lu

68 papers receiving 1.4k citations

Peers

Gary Lu
Comparison fields: 5 of 120
  • Applied Microbiology and Biotechnology 70
  • Hematology 383
  • Pathology and Forensic Medicine 385
  • Genetics 232
  • Biochemistry 119
Replace Yi‐Ying Wu with:
Yi‐Ying Wu Taiwan
Jianlin Qiao China
Paul C. Dimayuga United States
Katarzyna Guzińska-Ustymowicz Poland
Alan Kramer United States
Young Ok Jung South Korea
Kung‐Kai Kuo Taiwan
Shinichi Iwai Japan
Kenneth Ng United States
Olga Vitseva United States
Gary Lu relative to Yi‐Ying Wu Taiwan Yi‐Ying Wu's profile →
Citations per field
00.5×6.4×
Yi‐Ying Wu · 1×
Citations per year

Countries citing papers authored by Gary Lu

Since Specialization
Citations

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

Fields of papers citing papers by Gary Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010210
2 202093
3 201282
4
Population-based, case-control study of blood C-peptide level and breast cancer risk.
200173
5
Cancer prevention by tea and tea polyphenols.
200860
6 200454
7 201151
8 200351
9 201351
10 200848
11 201246
12 201043
13 201238
14 201435
15 200930
16 201429
17 201326
18 201326
19 201823
20 201521

About Gary Lu

Gary Lu is a scholar working on Hematology, Genetics, Pathology and Forensic Medicine, Oncology and Molecular Biology, having authored 69 papers that have together received 1.4k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (24 papers), Chronic Myeloid Leukemia Treatments (14 papers), Chronic Lymphocytic Leukemia Research (11 papers), Lymphoma Diagnosis and Treatment (9 papers), Acute Lymphoblastic Leukemia research (8 papers), Multiple Myeloma Research and Treatments (8 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers) and CAR-T cell therapy research (4 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (70 citations), Hematology (383 citations), Pathology and Forensic Medicine (385 citations), Genetics (232 citations) and Biochemistry (119 citations). Gary Lu has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include L. Jeffrey Medeiros, Chung S. Yang, Carlos E. Bueso‐Ramos, C. Cameron Yin, Hang Xiao, Huanyu Jin, Guang‐Yu Yang, Jie Liao, Zhé Hóu and Mao-Jung Lee. Their work appears in journals such as American Journal of Clinical Pathology, Blood, Leukemia Research, Annals of Oncology and Modern Pathology.

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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