M. Gee
Impact in
- Software top 5%
- Software Reliability and Analysis Research
-
- Cancer, Hypoxia, and Metabolism
Papers in
-
- Sarcoma Diagnosis and Treatment 3
- Co-authors
- David Malkin (6 shared papers)Miryung Kim (1 shared paper)Alex Loh (1 shared paper)Napol Rachatasumrit (1 shared paper)Bikul Das (2 shared papers)Rika Tsuchida (2 shared papers)Sylvain Baruchel (2 shared papers)Aru Narendran (4 shared papers)
- Journals
- Cancer Gene Therapy (2 papers)Macromolecules (1 paper)Cancer Research (1 paper)Pediatric Blood & Cancer (1 paper)Clinical Pharmacology & Therapeutics (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
M. Gee
15 papers receiving 500 citations
Peers
Comparison fields: 5 of 92
- Software 64
- Cancer Research 128
- Oncology 113
- Information Systems 89
- Molecular Biology 238
Countries citing papers authored by M. Gee
This map shows the geographic impact of M. Gee'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 M. Gee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Gee more than expected).
Fields of papers citing papers by M. Gee
This network shows the impact of papers produced by M. Gee. 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 M. Gee. The network helps show where M. Gee may publish in the future.
Co-authors
The 25 scholars most cited alongside M. Gee, 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 | 2005 | 100 | |
| 2 | 2010 | 96 | |
| 3 | 2005 | 73 | |
| 4 | An in vivo function for the transforming Myc protein: elicitation of the angiogenic phenotype. | 2000 | 63 |
| 5 | 2005 | 40 | |
| 6 | 2004 | 31 | |
| 7 | 2005 | 29 | |
| 8 | 2004 | 28 | |
| 9 | 1988 | 25 | |
| 10 | 2018 | 11 | |
| 11 | Energy analytics for development: big data for energy access, energy efficiency, and renewable energy | 2017 | 6 |
| 12 | 2023 | 5 | |
| 13 | 1992 | 2 | |
| 14 | 2022 | 1 | |
| 15 | 1989 | 1 | |
| 16 | 2024 | 0 | |
| 17 | 2025 | 0 |
About M. Gee
M. Gee is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Nuclear and High Energy Physics, Epidemiology and Hematology, having authored 17 papers that have together received 511 indexed citations. Recurring topics across this work include Quantum Chromodynamics and Particle Interactions (3 papers), Sarcoma Diagnosis and Treatment (3 papers), Cancer Research and Treatments (2 papers), Acute Myeloid Leukemia Research (2 papers), Virus-based gene therapy research (2 papers), Particle physics theoretical and experimental studies (2 papers), High-Energy Particle Collisions Research (2 papers) and Cancer, Hypoxia, and Metabolism (2 papers). The work is most often cited by research in Software (64 citations), Cancer Research (128 citations), Oncology (113 citations), Information Systems (89 citations) and Molecular Biology (238 citations). M. Gee has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include David Malkin, Miryung Kim, Alex Loh, Napol Rachatasumrit, Bikul Das, Rika Tsuchida, Sylvain Baruchel, Aru Narendran, Hooman Ganjavi and Claudia Eichler-Jonsson. Their work appears in journals such as Cancer Gene Therapy, Macromolecules, Cancer Research, Pediatric Blood & Cancer and Clinical Pharmacology & Therapeutics.
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.