John E. Garza
Impact in
- Hematology top 5%
- Acute Myeloid Leukemia Research
- Hematopoietic Stem Cell Transplantation
-
- Cancer Genomics and Diagnostics
Papers in
-
- Acute Myeloid Leukemia Research 2
- Genetics 2
- Genomic variations and chromosomal abnormalities 2
- Co-authors
- Lavi Oud (1 shared paper)Reagan A. Collins (1 shared paper)László Nagy (1 shared paper)Albin A John (1 shared paper)Ting Wang (2 shared papers)John Griswold (1 shared paper)Chad Tomlinson (2 shared papers)Derek Albracht (1 shared paper)
- Journals
- Nature Communications (2 papers)Nature Medicine (1 paper)Journal of Clinical Medicine (1 paper)Nature Methods (1 paper)New England Journal of Medicine (1 paper)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
John E. Garza
8 papers receiving 288 citations
John E. Garza's Hit Papers
Peers
Comparison fields: 5 of 33
- Hematology 181
- Cancer Research 31
- Genetics 44
- Public Health, Environmental and Occupational Health 28
- Genetics 7
Countries citing papers authored by John E. Garza
This map shows the geographic impact of John E. Garza'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 John E. Garza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John E. Garza more than expected).
Fields of papers citing papers by John E. Garza
This network shows the impact of papers produced by John E. Garza. 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 John E. Garza. The network helps show where John E. Garza may publish in the future.
Co-authors
The 11 scholars most cited alongside John E. Garza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Genome Sequencing as an Alternative to Cytogenetic Analysis in Myeloid Cancers Hit paper breakdown → | 2021 | 212 |
| 2 | 2022 | 59 | |
| 3 | 2024 | 7 | |
| 4 | 2025 | 4 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 2 | |
| 7 | 2026 | 2 | |
| 8 | 2026 | 1 | |
| 9 | 2026 | 0 | |
| 10 | 2026 | 0 | |
| 11 | 2026 | 0 |
About John E. Garza
John E. Garza is a scholar working on Hematology, Genetics, Epidemiology, Neurology and Molecular Biology, having authored 11 papers that have together received 290 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (3 papers), Acute Myeloid Leukemia Research (2 papers), Genomic variations and chromosomal abnormalities (2 papers), Burn Injury Management and Outcomes (1 paper), Epigenetics and DNA Methylation (1 paper), Traumatic Brain Injury and Neurovascular Disturbances (1 paper), Sepsis Diagnosis and Treatment (1 paper) and Autism Spectrum Disorder Research (1 paper). The work is most often cited by research in Hematology (181 citations), Cancer Research (31 citations), Genetics (44 citations), Public Health, Environmental and Occupational Health (28 citations) and Genetics (7 citations). John E. Garza has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Lavi Oud, Reagan A. Collins, László Nagy, Albin A John, Ting Wang, John Griswold, Chad Tomlinson, Derek Albracht, Xiaoyu Zhuo and Xiaoyun Xing. Their work appears in journals such as Nature Communications, Nature Medicine, Journal of Clinical Medicine, Nature Methods and New England Journal of Medicine.
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.