Patrick D. McGillivray

15.4k total citations
9 papers, 276 citations indexed

About

Patrick D. McGillivray is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Patrick D. McGillivray has authored 9 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Cancer Research and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Patrick D. McGillivray's work include Cancer Genomics and Diagnostics (5 papers), Renal cell carcinoma treatment (3 papers) and Renal and related cancers (3 papers). Patrick D. McGillivray is often cited by papers focused on Cancer Genomics and Diagnostics (5 papers), Renal cell carcinoma treatment (3 papers) and Renal and related cancers (3 papers). Patrick D. McGillivray collaborates with scholars based in United States, Denmark and Germany. Patrick D. McGillivray's co-authors include Mark Gerstein, Suganthi Balasubramanian, Russell Ault, Robert R. Kitchen, Sushant Kumar, Matthew Meyerson, Brian Shuch, Lucas Lochovsky, Shaoke Lou and Jakob Skou Pedersen and has published in prestigious journals such as Cell, Nucleic Acids Research and Nature Communications.

In The Last Decade

Patrick D. McGillivray

9 papers receiving 275 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Patrick D. McGillivray United States	7	212	96	52	46	29	9	276
Eliseos J. Mucaki Canada	11	214 1.0×	84 0.9×	42 0.8×	88 1.9×	62 2.1×	16	343
Yi Fang Guan Australia	8	191 0.9×	110 1.1×	32 0.6×	29 0.6×	33 1.1×	12	262
Tonje G. Lien Norway	9	260 1.2×	119 1.2×	38 0.7×	48 1.0×	72 2.5×	15	378
Stephanie Dorman United States	6	173 0.8×	74 0.8×	17 0.3×	24 0.5×	46 1.6×	13	282
Robert Wappel United States	6	166 0.8×	48 0.5×	39 0.8×	29 0.6×	75 2.6×	9	265
Rick Kim United States	5	247 1.2×	146 1.5×	41 0.8×	146 3.2×	45 1.6×	6	346
Masato Kimura United States	2	205 1.0×	74 0.8×	23 0.4×	111 2.4×	26 0.9×	2	324
Aaron Richardson United States	4	124 0.6×	58 0.6×	21 0.4×	25 0.5×	25 0.9×	5	189
Henry Paik United States	3	268 1.3×	88 0.9×	23 0.4×	82 1.8×	61 2.1×	3	323
Shu‐Hsuan Liu Taiwan	6	269 1.3×	177 1.8×	65 1.3×	16 0.3×	45 1.6×	7	356

Countries citing papers authored by Patrick D. McGillivray

Since Specialization

Citations

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

Fields of papers citing papers by Patrick D. McGillivray

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patrick D. McGillivray. 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 Patrick D. McGillivray. The network helps show where Patrick D. McGillivray may publish in the future.

Co-authorship network of co-authors of Patrick D. McGillivray

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

All Works

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9 of 9 papers shown

McGillivray, Patrick D., Daiki Ueno, Aydin Pooli, et al.. (2020). Distinguishing Benign Renal Tumors with an Oncocytic Gene Expression (ONEX) Classifier. European Urology. 79(1). 107–111. 14 indexed citations

Kumar, Sushant, Jonathan Warrell, Patrick D. McGillivray, et al.. (2020). Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences. Cell. 180(5). 915–927.e16. 94 indexed citations

Zhang, Jing, Jason Liu, Patrick D. McGillivray, et al.. (2020). NIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis. BMC Bioinformatics. 21(1). 474–474. 2 indexed citations

Shuch, Brian, Shantao Li, Harvey A. Risch, et al.. (2020). Estimation of the carrier frequency of fumarate hydratase alterations and implications for kidney cancer risk in hereditary leiomyomatosis and renal cancer. Cancer. 126(16). 3657–3666. 20 indexed citations

Ueno, Daiki, Zuoquan Xie, Marta Boeke, et al.. (2018). Genomic Heterogeneity and the Small Renal Mass. Clinical Cancer Research. 24(17). 4137–4144. 13 indexed citations

Kumar, Sushant, Patrick D. McGillivray, Matthew Meyerson, et al.. (2018). Abstract 1279: Passenger mutation landscape in cancer genomes. Cancer Research. 78(13_Supplement). 1279–1279. 2 indexed citations

McGillivray, Patrick D., Declan Clarke, Matthew Meyerson, et al.. (2018). Network Analysis as a Grand Unifier in Biomedical Data Science. 1(1). 153–180. 25 indexed citations

McGillivray, Patrick D., et al.. (2018). A comprehensive catalog of predicted functional upstream open reading frames in humans. Nucleic Acids Research. 46(7). 3326–3338. 78 indexed citations

Balasubramanian, Suganthi, Yao Fu, Patrick D. McGillivray, et al.. (2017). Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes. Nature Communications. 8(1). 382–382. 28 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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