Aaron McGeever

5.8k total citations
10 papers, 109 citations indexed

About

Aaron McGeever is a scholar working on Molecular Biology, Infectious Diseases and Biophysics. According to data from OpenAlex, Aaron McGeever has authored 10 papers receiving a total of 109 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Infectious Diseases and 3 papers in Biophysics. Recurrent topics in Aaron McGeever's work include Single-cell and spatial transcriptomics (4 papers), COVID-19 epidemiological studies (3 papers) and Cell Image Analysis Techniques (3 papers). Aaron McGeever is often cited by papers focused on Single-cell and spatial transcriptomics (4 papers), COVID-19 epidemiological studies (3 papers) and Cell Image Analysis Techniques (3 papers). Aaron McGeever collaborates with scholars based in United States, Japan and United Kingdom. Aaron McGeever's co-authors include Angela Oliveira Pisco, Jure Leskovec, Krista McCutcheon, Maria Brbić, Russ B. Altman, Sheng Wang, Norma Neff, Natalia Friedland, Spyros Darmanis and Peter Kim and has published in prestigious journals such as Nature Communications, Nature Genetics and Neurology.

In The Last Decade

Aaron McGeever

10 papers receiving 107 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aaron McGeever United States	6	55	30	16	16	15	10	109
Mardiana Marzuki Singapore	4	57 1.0×	56 1.9×	5 0.3×	2 0.1×	8 0.5×	5	132
Morgan Essex Germany	4	143 2.6×	27 0.9×	1 0.1×	4 0.3×	5 0.3×	5	182
Xiaofei Zhao China	5	55 1.0×	18 0.6×	6 0.4×	2 0.1×	1 0.1×	18	114
Krupa Navalkar United States	5	90 1.6×	34 1.1×		10 0.6×		9	158
Qiaoxing Liang China	8	114 2.1×	10 0.3×	1 0.1×	4 0.3×	4 0.3×	11	201
Glykeria Vlachogianni Greece	3	21 0.4×	20 0.7×	2 0.1×	3 0.2×		5	76
Jacob H. Elnaggar United States	6	46 0.8×	40 1.3×		4 0.3×		15	122
Bremy Alburquerque United States	4	93 1.7×	4 0.1×	6 0.4×	6 0.4×	1 0.1×	7	112
Blanka Andersson Sweden	6	42 0.8×	67 2.2×	2 0.1×	4 0.3×	2 0.1×	11	142
Daniel Chen United States	7	50 0.9×	15 0.5×		2 0.1×	2 0.1×	12	134

Countries citing papers authored by Aaron McGeever

Since Specialization

Citations

This map shows the geographic impact of Aaron McGeever'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 Aaron McGeever with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron McGeever more than expected).

Fields of papers citing papers by Aaron McGeever

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aaron McGeever. 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 Aaron McGeever. The network helps show where Aaron McGeever may publish in the future.

Co-authorship network of co-authors of Aaron McGeever

This figure shows the co-authorship network connecting the top 25 collaborators of Aaron McGeever. A scholar is included among the top collaborators of Aaron McGeever 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 Aaron McGeever. Aaron McGeever is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Borja, Michael, Vanessa Tran, Alejandro A. Granados, et al.. (2025). Single-nucleus RNA sequencing reveals a preclinical model for the most common subtype of glioblastoma. Communications Biology. 8(1). 671–671. 3 indexed citations

2.

Ergen, Can, Galen Xing, Chenling Xu, et al.. (2024). Consensus prediction of cell type labels in single-cell data with popV. Nature Genetics. 56(12). 2731–2738. 5 indexed citations

3.

Treut, Guillaume Le, Greg Huber, Aaron McGeever, et al.. (2022). A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies. Scientific Reports. 12(1). 15946–15946. 2 indexed citations

4.

Serpa, Paula Hayakawa, Xianding Deng, Mazin Abdelghany, et al.. (2022). Metagenomic prediction of antimicrobial resistance in critically ill patients with lower respiratory tract infections. Genome Medicine. 14(1). 74–74. 46 indexed citations

5.

Wang, Sheng, Angela Oliveira Pisco, Aaron McGeever, et al.. (2021). Leveraging the Cell Ontology to classify unseen cell types. Nature Communications. 12(1). 5556–5556. 26 indexed citations

6.

Huber, Greg, et al.. (2021). A minimal model for household-based testing and tracing in epidemics. Physical Biology. 18(4). 45002–45002. 1 indexed citations

7.

Huber, Greg, et al.. (2021). A random-walk-based epidemiological model. Scientific Reports. 11(1). 19308–19308. 5 indexed citations

8.

Pisco, Angela Oliveira, et al.. (2021). Single-Cell Analysis for Whole-Organism Datasets. PubMed. 4(1). 207–226. 5 indexed citations

9.

Waltari, Eric, Aaron McGeever, Natalia Friedland, Peter Kim, & Krista McCutcheon. (2019). Functional Enrichment and Analysis of Antigen-Specific Memory B Cell Antibody Repertoires in PBMCs. Frontiers in Immunology. 10. 1452–1452. 15 indexed citations

10.

Ramachandran, Prashanth, Fiona V Cresswell, Charles Langelier, et al.. (2019). Illuminating Tuberculosis Meningitis with Metagenomics and FLASH Enrichment (S45.005). Neurology. 92(15_supplement). 1 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.

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