M. Gee

810 citations
19 papers · 541 · h-index 10

Impact in

  • Software top 5%
    • Software Reliability and Analysis Research
    • Software Testing and Debugging Techniques
    • Cancer, Hypoxia, and Metabolism

Papers in

M. Gee

17 papers receiving 528 citations

Peers

M. Gee
Comparison fields: 5 of 90
  • Software 72
  • Cancer Research 112
  • Information Systems 100
  • Oncology 97
  • Molecular Biology 212
Replace Benoît Langlois with:
Benoît Langlois France
Shih‐Yu Chen Taiwan
Richard Melton United States
Qiurong Liu China
Kouhei Sakurai Japan
Xiaoji Chen United States
Andrew D. Kelly United States
Matthias Pfeifer Germany
H. Zhong United States
Olga Nikolova United States
M. Gee relative to Benoît Langlois France Benoît Langlois's profile →
Citations per field
00.5×2.7×
Benoît Langlois · 1×
Citations per year

Countries citing papers authored by M. Gee

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with M. Gee Line = papers co-authored together M. Gee links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2010107
2 2005105
3 200574
4
An in vivo function for the transforming Myc protein: elicitation of the angiogenic phenotype.
200066
5 200540
6 200435
7 200529
8 200429
9 198825
10 201812
11 20236
12
Energy analytics for development: big data for energy access, energy efficiency, and renewable energy
20176
13 20222
14 19922
15 20251
16 20231
17 19891
18 20240
19 20260

About M. Gee

M. Gee is a scholar working on Molecular Biology, Epidemiology, Nuclear and High Energy Physics, Pulmonary and Respiratory Medicine and Genetics, having authored 19 papers that have together received 541 indexed citations. Recurring topics across this work include Quantum Chromodynamics and Particle Interactions (3 papers), Liver Disease Diagnosis and Treatment (3 papers), Sarcoma Diagnosis and Treatment (2 papers), Angiogenesis and VEGF in Cancer (2 papers), Particle physics theoretical and experimental studies (2 papers), High-Energy Particle Collisions Research (2 papers), Cancer Research and Treatments (2 papers) and Cancer, Hypoxia, and Metabolism (2 papers). The work is most often cited by research in Software (72 citations), Cancer Research (112 citations), Information Systems (100 citations), Oncology (97 citations) and Molecular Biology (212 citations). M. Gee has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include David Malkin, Alex Loh, Napol Rachatasumrit, Miryung Kim, Sylvain Baruchel, Bikul Das, Rika Tsuchida, Aru Narendran, Hooman Ganjavi and Risa Torkin. Their work appears in journals such as Cancer Gene Therapy, Clinica Chimica Acta, Oncogene, Multiple Sclerosis Journal and Cancer Research.

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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