Monica McAndrews

2.8k total citations
10 papers, 772 citations indexed

About

Monica McAndrews is a scholar working on Molecular Biology, Cancer Research and Cell Biology. According to data from OpenAlex, Monica McAndrews has authored 10 papers receiving a total of 772 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Cancer Research and 2 papers in Cell Biology. Recurrent topics in Monica McAndrews's work include Signaling Pathways in Disease (2 papers), Protease and Inhibitor Mechanisms (2 papers) and Genomics and Phylogenetic Studies (2 papers). Monica McAndrews is often cited by papers focused on Signaling Pathways in Disease (2 papers), Protease and Inhibitor Mechanisms (2 papers) and Genomics and Phylogenetic Studies (2 papers). Monica McAndrews collaborates with scholars based in United States, United Kingdom and Canada. Monica McAndrews's co-authors include Daniel W. Nebert, David C. Thompson, Vasilis Vasiliou, Elspeth A. Bruford, Brian C. Jackson, Matt W. Wright, Sudha Swamynathan, Shivalingappa K. Swamynathan, Gary A. Silverman and Claire Heit and has published in prestigious journals such as The Journal of Immunology, Scientific Reports and Trends in Genetics.

In The Last Decade

Monica McAndrews

10 papers receiving 764 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Monica McAndrews United States	10	397	222	116	93	83	10	772
Artem Smirnov Italy	14	576 1.5×	194 0.9×	92 0.8×	176 1.9×	87 1.0×	34	953
Hendrik J.M. de Jonge Netherlands	11	684 1.7×	175 0.8×	111 1.0×	90 1.0×	111 1.3×	20	999
James Wettenhall Australia	8	562 1.4×	152 0.7×	238 2.1×	100 1.1×	134 1.6×	9	1.1k
Luigi Grassi Italy	14	559 1.4×	237 1.1×	123 1.1×	74 0.8×	104 1.3×	41	859
Mingxiong Guo China	19	742 1.9×	383 1.7×	106 0.9×	98 1.1×	63 0.8×	47	1.0k
So‐Hee Hong South Korea	18	381 1.0×	102 0.5×	249 2.1×	118 1.3×	101 1.2×	50	931
Irina A. Eliseeva Russia	17	1.0k 2.5×	213 1.0×	143 1.2×	94 1.0×	63 0.8×	36	1.2k
Yinan Wang China	18	633 1.6×	199 0.9×	236 2.0×	83 0.9×	68 0.8×	42	992

Countries citing papers authored by Monica McAndrews

Since Specialization

Citations

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

Fields of papers citing papers by Monica McAndrews

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Monica McAndrews

This figure shows the co-authorship network connecting the top 25 collaborators of Monica McAndrews. A scholar is included among the top collaborators of Monica McAndrews 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 Monica McAndrews. Monica McAndrews 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

Seal, Ruth L., Paul Denny, Elspeth A. Bruford, et al.. (2022). A standardized nomenclature for mammalian histone genes. Epigenetics & Chromatin. 15(1). 34–34. 32 indexed citations

Dolan, M. Eileen, David P. Hill, Gaurab Mukherjee, et al.. (2020). Investigation of COVID-19 comorbidities reveals genes and pathways coincident with the SARS-CoV-2 viral disease. Scientific Reports. 10(1). 20848–20848. 27 indexed citations

Hill, David P., Joan Malcolm, Monica McAndrews, et al.. (2019). Cisplatin-resistant triple-negative breast cancer subtypes: multiple mechanisms of resistance. BMC Cancer. 19(1). 1039–1039. 87 indexed citations

Charkoftaki, Georgia, Yewei Wang, Monica McAndrews, et al.. (2019). Update on the human and mouse lipocalin (LCN) gene family, including evidence the mouse Mup cluster is result of an “evolutionary bloom”. Human Genomics. 13(1). 57 indexed citations

Bruford, Elspeth A., et al.. (2016). Organization, evolution and functions of the human and mouse Ly6/uPAR family genes. Human Genomics. 10(1). 10–10. 144 indexed citations

Kubagawa, Hiromi, Michael C. Carroll, Chaim O. Jacob, et al.. (2015). Nomenclature of Toso, Fas Apoptosis Inhibitory Molecule 3, and IgM FcR. The Journal of Immunology. 194(9). 4055–4057. 14 indexed citations

Desvignes, Thomas, Peter Batzel, Eugène Berezikov, et al.. (2015). miRNA Nomenclature: A View Incorporating Genetic Origins, Biosynthetic Pathways, and Sequence Variants. Trends in Genetics. 31(11). 613–626. 147 indexed citations

Dolan, M. Eileen, Richard M. Baldarelli, Susan M. Bello, et al.. (2015). Orthology for comparative genomics in the mouse genome database. Mammalian Genome. 26(7-8). 305–313. 9 indexed citations

Heit, Claire, Brian C. Jackson, Monica McAndrews, et al.. (2013). Update of the human and mouse SERPINgene superfamily. Human Genomics. 7(1). 22–22. 183 indexed citations

10.

Jackson, Brian C., David C. Thompson, Matt W. Wright, et al.. (2011). Update of the human secretoglobin (SCGB) gene superfamily and an example of 'evolutionary bloom' of androgen-binding protein genes within the mouse Scgb gene superfamily. Human Genomics. 5(6). 691–691. 72 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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