Matthew McCoy

843 total citations
32 papers, 439 citations indexed

About

Matthew McCoy is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Matthew McCoy has authored 32 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 12 papers in Oncology and 10 papers in Cancer Research. Recurrent topics in Matthew McCoy's work include Cancer Genomics and Diagnostics (9 papers), Computational Drug Discovery Methods (4 papers) and Bioinformatics and Genomic Networks (4 papers). Matthew McCoy is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Computational Drug Discovery Methods (4 papers) and Bioinformatics and Genomic Networks (4 papers). Matthew McCoy collaborates with scholars based in United States, Malaysia and United Kingdom. Matthew McCoy's co-authors include Subha Madhavan, Stephen W. Byers, Ivana Peran, M. Saleet Jafri, Dmitri K. Klimov, Sridhar Nimmagadda, Lü Jin, Suzanne J. Bakewell, Charles M. Rudin and Viola Allaj and has published in prestigious journals such as Journal of Clinical Investigation, Blood and Gastroenterology.

In The Last Decade

Matthew McCoy

29 papers receiving 436 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew McCoy United States 12 217 163 104 80 75 32 439
Jaafar Makki Malaysia 6 193 0.9× 148 0.9× 136 1.3× 51 0.6× 33 0.4× 8 431
Katsuya Nakai Japan 12 369 1.7× 336 2.1× 168 1.6× 52 0.7× 50 0.7× 29 656
Ingrid Babel Spain 8 137 0.6× 301 1.8× 84 0.8× 135 1.7× 60 0.8× 9 483
Nicholas P. McAndrew United States 10 272 1.3× 136 0.8× 119 1.1× 88 1.1× 27 0.4× 34 432
Mary Luz Uribe Spain 8 153 0.7× 259 1.6× 81 0.8× 33 0.4× 35 0.5× 14 513
Hima Patel United States 12 277 1.3× 383 2.3× 74 0.7× 86 1.1× 78 1.0× 20 682
Yin Gu United States 13 137 0.6× 211 1.3× 95 0.9× 30 0.4× 164 2.2× 23 491
Aleksandra Wroblewska Netherlands 12 163 0.8× 255 1.6× 38 0.4× 95 1.2× 131 1.7× 17 606
David Mysona United States 9 104 0.5× 202 1.2× 112 1.1× 69 0.9× 57 0.8× 25 419

Countries citing papers authored by Matthew McCoy

Since Specialization
Citations

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

Fields of papers citing papers by Matthew McCoy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew McCoy

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

All Works

20 of 20 papers shown
1.
McCoy, Matthew, Chen‐Hsiang Yeang, Stanley Tam, et al.. (2025). Generalized Evolutionary Classifier for Evolutionary Guided Precision Medicine. JCO Precision Oncology. 9(9). e2300714–e2300714. 1 indexed citations
2.
He, Wei, Matthew McCoy, Rebecca B. Riggins, Robert A. Beckman, & Chen-Hsiang Yeang. (2025). Personalized cancer treatment strategies incorporating irreversible and reversible drug resistance mechanisms. npj Systems Biology and Applications. 11(1). 70–70. 1 indexed citations
3.
McCoy, Matthew. (2025). Digital twins in oncology: where we are and where we hope to go. PubMed. 4(1). e000893–e000893.
4.
5.
Shobab, Leila, Kirk Jensen, Matthew McCoy, et al.. (2024). Sex-Specific Expression of Histone Lysine Demethylases (KDMs) in Thyroid Cancer. Cancers. 16(7). 1260–1260. 2 indexed citations
6.
Shobab, Leila, Matthew McCoy, Sonam Kumari, et al.. (2024). PD-L1 Expression Varies in Thyroid Cancer Types and Is Associated with Decreased Progression Free Survival (PFS) in Patients with Anaplastic Thyroid Cancer. Cancers. 16(21). 3632–3632. 2 indexed citations
7.
Jin, Lü, Stanley Tam, Manasi Balachandran, et al.. (2023). Unraveling Vulnerabilities in Endocrine Therapy-Resistant HER2+/ER+ Breast Cancer. Endocrinology. 164(12). 5 indexed citations
8.
Chang, Hung-Ching, et al.. (2023). Understanding the need for digital twins’ data in patient advocacy and forecasting oncology. Frontiers in Artificial Intelligence. 6. 1260361–1260361. 10 indexed citations
9.
Niro, Roberto Di, Carl Pelz, Aditi Jain, et al.. (2022). The RNA-Binding Protein HuR Posttranscriptionally Regulates the Protumorigenic Activator YAP1 in Pancreatic Ductal Adenocarcinoma. Molecular and Cellular Biology. 42(7). e0001822–e0001822. 9 indexed citations
10.
Klimov, Dmitri K., et al.. (2021). Machine learning-based prediction of drug and ligand binding in BCL-2 variants through molecular dynamics. Computers in Biology and Medicine. 140. 105060–105060. 13 indexed citations
11.
Gomes-Lima, Cristiane, Leila Shobab, Di Wu, et al.. (2021). Do Molecular Profiles of Primary Versus Metastatic Radioiodine Refractory Differentiated Thyroid Cancer Differ?. Frontiers in Endocrinology. 12. 623182–623182. 13 indexed citations
12.
Bakewell, Suzanne J., Isabel Conde, Yassi Fallah, et al.. (2020). Inhibition of DNA Repair Pathways and Induction of ROS Are Potential Mechanisms of Action of the Small Molecule Inhibitor BOLD-100 in Breast Cancer. Cancers. 12(9). 2647–2647. 37 indexed citations
13.
Peran, Ivana, Sivanesan Dakshanamurthy, Matthew McCoy, et al.. (2020). Cadherin 11 Promotes Immunosuppression and Extracellular Matrix Deposition to Support Growth of Pancreatic Tumors and Resistance to Gemcitabine in Mice. Gastroenterology. 160(4). 1359–1372.e13. 67 indexed citations
14.
McGarvey, Peter B., Jiahao Huang, Matthew McCoy, et al.. (2020). De novo assembly and annotation of transcriptomes from two cultivars of Cannabis sativa with different cannabinoid profiles. Gene. 762. 145026–145026. 12 indexed citations
15.
McCoy, Matthew, Subha Madhavan, Sridhar Nimmagadda, Dmitri K. Klimov, & M. Saleet Jafri. (2019). Translational Applications of Protein Structure Simulation: Predicting Phenotype of Missense Variants. Biophysical Journal. 116(3). 13a–13a. 3 indexed citations
16.
McCoy, Matthew, et al.. (2019). SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants. BMC Bioinformatics. 20(1). 171–171. 8 indexed citations
17.
Peran, Ivana, Subha Madhavan, Stephen W. Byers, & Matthew McCoy. (2018). Curation of the Pancreatic Ductal Adenocarcinoma Subset of the Cancer Genome Atlas Is Essential for Accurate Conclusions about Survival-Related Molecular Mechanisms. Clinical Cancer Research. 24(16). 3813–3819. 47 indexed citations
18.
Danos, Arpad, Deborah Ritter, Alex H. Wagner, et al.. (2018). Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community‐driven standards. Human Mutation. 39(11). 1721–1732. 12 indexed citations
19.
Kumar, Dhiraj, Ala Lisok, Elyes Dahmane, et al.. (2018). Peptide-based PET quantifies target engagement of PD-L1 therapeutics. Journal of Clinical Investigation. 129(2). 616–630. 103 indexed citations
20.
Zera, Richard T., Joan M. Van Camp, Matthew McCoy, et al.. (2001). Atypical hyperplasia, proliferative fibrocystic change, and exogenous hormone use. Surgery. 130(4). 732–737. 3 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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