Gregory McAllister
Impact in
- Aging top 5%
Papers in
-
- CRISPR and Genetic Engineering 5
- Gene Regulatory Network Analysis 3
- Gene expression and cancer classification 2
- Machine Learning in Bioinformatics 1
-
- Autophagy in Disease and Therapy 3
- Co-authors
- Gregory R. Hoffman (6 shared papers)Elizabeth Frias (3 shared papers)Carsten Russ (5 shared papers)John Reece-Hoyes (4 shared papers)Daniel Ho (2 shared papers)Ranjit Randhawa (2 shared papers)Chaoyang Ye (2 shared papers)Ajamete Kaykas (2 shared papers)
- Journals
- Cell Reports (2 papers)Proceedings of the National Academy of Sciences (2 papers)SLAS DISCOVERY (1 paper)Nature Medicine (1 paper)The Journal of Cell Biology (1 paper)
- Partner nations
- SwitzerlandUnited StatesChina
In The Last Decade
Gregory McAllister
17 papers receiving 1.5k citations
Gregory McAllister's Hit Papers
Peers
Comparison fields: 5 of 88
- Aging 68
- Business and International Management 71
- Molecular Biology 1.1k
- Physiology 72
- Biophysics 56
Countries citing papers authored by Gregory McAllister
This map shows the geographic impact of Gregory McAllister'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 Gregory McAllister with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregory McAllister more than expected).
Fields of papers citing papers by Gregory McAllister
This network shows the impact of papers produced by Gregory McAllister. 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 Gregory McAllister. The network helps show where Gregory McAllister may publish in the future.
Co-authors
The 25 scholars most cited alongside Gregory McAllister, 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 | p53 inhibits CRISPR–Cas9 engineering in human pluripotent stem cells Hit paper breakdown → | 2018 | 658 |
| 2 | 2015 | 194 | |
| 3 | 2017 | 140 | |
| 4 | 2018 | 135 | |
| 5 | 2017 | 74 | |
| 6 | 2017 | 63 | |
| 7 | 2016 | 61 | |
| 8 | 2015 | 43 | |
| 9 | 2016 | 34 | |
| 10 | 2011 | 33 | |
| 11 | 2012 | 23 | |
| 12 | 2018 | 10 | |
| 13 | 2002 | 9 | |
| 14 | 2012 | 9 | |
| 15 | 2005 | 4 | |
| 16 | 2008 | 3 | |
| 17 | 2018 | 2 |
About Gregory McAllister
Gregory McAllister is a scholar working on Molecular Biology, Epidemiology, Public Health, Environmental and Occupational Health, Pulmonary and Respiratory Medicine and Computational Theory and Mathematics, having authored 17 papers that have together received 1.5k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (5 papers), Gene Regulatory Network Analysis (3 papers), Autophagy in Disease and Therapy (3 papers), Mosquito-borne diseases and control (2 papers), Computational Drug Discovery Methods (2 papers), Insect symbiosis and bacterial influences (2 papers), Gene expression and cancer classification (2 papers) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Aging (68 citations), Business and International Management (71 citations), Molecular Biology (1.1k citations), Physiology (72 citations) and Biophysics (56 citations). Gregory McAllister has collaborated with scholars based in Switzerland, United States and China. Frequent co-authors include Gregory R. Hoffman, Elizabeth Frias, Carsten Russ, John Reece-Hoyes, Daniel Ho, Ranjit Randhawa, Chaoyang Ye, Ajamete Kaykas, Robert J. Ihry and Zinger Yang. Their work appears in journals such as Cell Reports, Proceedings of the National Academy of Sciences, SLAS DISCOVERY, Nature Medicine and The Journal of Cell Biology.
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.