Gregory McAllister

4.3k total citations · 1 hit paper
17 papers, 1.5k citations indexed

About

Gregory McAllister is a scholar working on Molecular Biology, Epidemiology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Gregory McAllister has authored 17 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Epidemiology and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Gregory McAllister's work include CRISPR and Genetic Engineering (5 papers), Gene Regulatory Network Analysis (3 papers) and Autophagy in Disease and Therapy (3 papers). Gregory McAllister is often cited by papers focused on CRISPR and Genetic Engineering (5 papers), Gene Regulatory Network Analysis (3 papers) and Autophagy in Disease and Therapy (3 papers). Gregory McAllister collaborates with scholars based in Switzerland, United States and China. Gregory McAllister's co-authors include Gregory R. Hoffman, Elizabeth Frias, Carsten Russ, John Reece-Hoyes, Daniel Ho, Ranjit Randhawa, Robert J. Ihry, Chaoyang Ye, Ajamete Kaykas and Zinger Yang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Medicine.

In The Last Decade

Gregory McAllister

17 papers receiving 1.5k citations

Hit Papers

p53 inhibits CRISPR–Cas9 engineering in human pluripotent... 2018 2026 2020 2023 2018 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gregory McAllister Switzerland 11 1.1k 335 224 163 123 17 1.5k
Yorick Post Netherlands 8 1.3k 1.1× 71 0.2× 232 1.0× 240 1.5× 115 0.9× 16 1.6k
Rajat Gupta Denmark 14 1.8k 1.6× 192 0.6× 219 1.0× 326 2.0× 412 3.3× 15 2.2k
Irma Lemmens Belgium 19 1.3k 1.2× 516 1.5× 243 1.1× 441 2.7× 304 2.5× 42 2.1k
David P. Davis United States 18 1.1k 0.9× 257 0.8× 121 0.5× 254 1.6× 234 1.9× 29 1.5k
Lina Abi-Mosleh United States 9 800 0.7× 235 0.7× 84 0.4× 100 0.6× 402 3.3× 9 1.7k
Joppe Nieuwenhuis Netherlands 12 962 0.8× 193 0.6× 165 0.7× 121 0.7× 333 2.7× 13 1.4k
Adam Oberstein United States 12 957 0.8× 630 1.9× 122 0.5× 113 0.7× 184 1.5× 13 1.5k
Axel Choidas Germany 16 1.4k 1.2× 147 0.4× 89 0.4× 170 1.0× 209 1.7× 30 2.0k
Marcello Maresca Sweden 21 1.4k 1.3× 78 0.2× 485 2.2× 86 0.5× 42 0.3× 36 1.7k
Ulrich Elling Austria 17 1.1k 1.0× 55 0.2× 231 1.0× 96 0.6× 76 0.6× 37 1.4k

Countries citing papers authored by Gregory McAllister

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Gregory McAllister

This figure shows the co-authorship network connecting the top 25 collaborators of Gregory McAllister. A scholar is included among the top collaborators of Gregory McAllister based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gregory McAllister. Gregory McAllister is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Hoepfner, Dominic, Gregory McAllister, & Gregory R. Hoffman. (2018). CRISPR/Cas9-Based Chemogenomic Profiling in Mammalian Cells. Methods in molecular biology. 1888. 153–174. 2 indexed citations
2.
Ihry, Robert J., Kathleen A. Worringer, Max R. Salick, et al.. (2018). p53 inhibits CRISPR–Cas9 engineering in human pluripotent stem cells. Nature Medicine. 24(7). 939–946. 658 indexed citations breakdown →
3.
Wang, Zhao, Nicole Renaud, Zinger Yang, et al.. (2018). TRRAP is a central regulator of human multiciliated cell formation. The Journal of Cell Biology. 217(6). 1941–1955. 10 indexed citations
4.
Ye, Chaoyang, Daniel Ho, Marilisa Neri, et al.. (2018). DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery. Nature Communications. 9(1). 4307–4307. 135 indexed citations
5.
Estoppey, David, Boon Heng Lee, Kah Fei Wan, et al.. (2017). The Natural Product Cavinafungin Selectively Interferes with Zika and Dengue Virus Replication by Inhibition of the Host Signal Peptidase. Cell Reports. 19(3). 451–460. 63 indexed citations
6.
Goodwin, Jonathan M., William E. Dowdle, Zuncai Wang, et al.. (2017). Autophagy-Independent Lysosomal Targeting Regulated by ULK1/2-FIP200 and ATG9. Cell Reports. 20(10). 2341–2356. 140 indexed citations
7.
Potting, Christoph, Christophe Crochemore, Francesca Moretti, et al.. (2017). Genome-wide CRISPR screen for PARKIN regulators reveals transcriptional repression as a determinant of mitophagy. Proceedings of the National Academy of Sciences. 115(2). E180–E189. 74 indexed citations
8.
Wang, Yuan, et al.. (2016). Evidence-Based and Quantitative Prioritization of Tool Compounds in Phenotypic Drug Discovery. Cell chemical biology. 23(7). 862–874. 34 indexed citations
9.
Wang, Hui, Bo Lü, Yue Zhang, et al.. (2016). Tankyrase Inhibitor Sensitizes Lung Cancer Cells to Endothelial Growth Factor Receptor (EGFR) Inhibition via Stabilizing Angiomotins and Inhibiting YAP Signaling. Journal of Biological Chemistry. 291(29). 15256–15266. 61 indexed citations
10.
Lantermann, Alexandra B., Dongshu Chen, Greg Hoffman, et al.. (2015). Inhibition of Casein Kinase 1 Alpha Prevents Acquired Drug Resistance to Erlotinib in EGFR-Mutant Non–Small Cell Lung Cancer. Cancer Research. 75(22). 4937–4948. 43 indexed citations
11.
Eng, Christina H., Zuncai Wang, Diane Tkach, et al.. (2015). Macroautophagy is dispensable for growth of KRAS mutant tumors and chloroquine efficacy. Proceedings of the National Academy of Sciences. 113(1). 182–187. 194 indexed citations
12.
Hutz, Janna, Thomas Nelson, Hua Wu, et al.. (2012). The Multidimensional Perturbation Value: A Single Metric to Measure Similarity and Activity of Treatments in High-Throughput Multidimensional Screens. SLAS DISCOVERY. 18(4). 367–377. 23 indexed citations
13.
Nigsch, Florian, Janna Hutz, Douglas W. Selinger, et al.. (2012). Determination of minimal transcriptional signatures of compounds for target prediction. PubMed. 2012(1). 2–2. 9 indexed citations
14.
Bland, Nicholas D., Cuihua Wang, Zhouxi Wang, et al.. (2011). Pharmacological Validation of Trypanosoma brucei Phosphodiesterases B1 and B2 as Druggable Targets for African Sleeping Sickness. Journal of Medicinal Chemistry. 54(23). 8188–8194. 33 indexed citations
15.
Martini, Paolo, Deanne Taylor, Jadwiga Biénkowska, et al.. (2008). Comparative expression analysis of four breast cancer subtypes versus matched normal tissue from the same patients. The Journal of Steroid Biochemistry and Molecular Biology. 109(3-5). 207–211. 3 indexed citations
16.
Zhang, Ruisheng, et al.. (2005). Coupling Wavelet Transform with Bayesian Network to Classify Auditory Brainstem Responses. PubMed. 2. 7568–7571. 4 indexed citations
17.
McAllister, Gregory, et al.. (2002). Triage protein fold prediction. Proteins Structure Function and Bioinformatics. 48(4). 654–663. 9 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026