Owen M. Wilkins

969 total citations
18 papers, 658 citations indexed

About

Owen M. Wilkins is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Owen M. Wilkins has authored 18 papers receiving a total of 658 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 9 papers in Cancer Research and 7 papers in Oncology. Recurrent topics in Owen M. Wilkins's work include RNA modifications and cancer (5 papers), Epigenetics and DNA Methylation (4 papers) and Cancer Cells and Metastasis (4 papers). Owen M. Wilkins is often cited by papers focused on RNA modifications and cancer (5 papers), Epigenetics and DNA Methylation (4 papers) and Cancer Cells and Metastasis (4 papers). Owen M. Wilkins collaborates with scholars based in United States, Netherlands and Australia. Owen M. Wilkins's co-authors include Brock C. Christensen, Lucas A. Salas, Katharine M. von Herrmann, Joseph M. Howard, Matthew C. Havrda, Stephen Lee, Alison L. Young, William F. Hickey, Matthew Ung and Manabu Kurokawa and has published in prestigious journals such as PLoS ONE, Analytical Biochemistry and Science Advances.

In The Last Decade

Owen M. Wilkins

17 papers receiving 652 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Owen M. Wilkins United States	11	463	203	194	54	53	18	658
Shruti Desai United States	13	476 1.0×	208 1.0×	144 0.7×	109 2.0×	27 0.5×	28	692
Leire Moreno‐Cugnon Spain	12	311 0.7×	193 1.0×	86 0.4×	32 0.6×	65 1.2×	17	557
Alex Campos United States	11	426 0.9×	161 0.8×	95 0.5×	98 1.8×	64 1.2×	17	638
Leanne Li United States	7	341 0.7×	212 1.0×	140 0.7×	46 0.9×	30 0.6×	10	580
Miriam Rábano Spain	9	467 1.0×	172 0.8×	265 1.4×	16 0.3×	27 0.5×	17	689
Cécile Thirant France	13	408 0.9×	170 0.8×	141 0.7×	49 0.9×	14 0.3×	18	594
Qing Ouyang China	13	279 0.6×	145 0.7×	87 0.4×	41 0.8×	25 0.5×	19	471
Jayanth Krishnan United States	3	541 1.2×	135 0.7×	79 0.4×	37 0.7×	20 0.4×	5	736
Francis N. Saridin Netherlands	7	329 0.7×	106 0.5×	262 1.4×	19 0.4×	66 1.2×	9	608
Yunhong Zha China	19	764 1.7×	348 1.7×	153 0.8×	70 1.3×	56 1.1×	35	1.1k

Countries citing papers authored by Owen M. Wilkins

Since Specialization

Citations

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

Fields of papers citing papers by Owen M. Wilkins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Owen M. Wilkins. 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 Owen M. Wilkins. The network helps show where Owen M. Wilkins may publish in the future.

Co-authorship network of co-authors of Owen M. Wilkins

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

All Works

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18 of 18 papers shown

Reisz, Julie A., Sukrut C. Kamerkar, Rachel Culp‐Hill, et al.. (2025). Targeting pyruvate metabolism generates distinct CD8+ T cell responses to gammaherpesvirus and B lymphoma. JCI Insight. 10(16).

Wilkins, Owen M., et al.. (2024). Cloud-based introduction to BASH programming for biologists. Briefings in Bioinformatics. 25(Supplement_1). 1 indexed citations

Kolling, Fred, Owen M. Wilkins, Subhadeep Das, et al.. (2024). Pharmacological induction of chromatin remodeling drives chemosensitization in triple-negative breast cancer. Cell Reports Medicine. 5(4). 101504–101504. 10 indexed citations

Lee, Min Kyung, et al.. (2023). Lineage plasticity enables low-ER luminal tumors to evolve and gain basal-like traits. Breast Cancer Research. 25(1). 23–23. 14 indexed citations

Wilkins, Owen M., Chenyang Li, Fred Kolling, et al.. (2023). Characterizing control of memory CD8 T cell differentiation by BTB-ZF transcription factor Zbtb20. Life Science Alliance. 6(9). e202201683–e202201683. 4 indexed citations

Brown, Meredith S., Behnaz Abdollahi, Owen M. Wilkins, et al.. (2022). Phenotypic heterogeneity driven by plasticity of the intermediate EMT state governs disease progression and metastasis in breast cancer. Science Advances. 8(31). eabj8002–eabj8002. 79 indexed citations

Brown, Meredith S., et al.. (2022). Distinct Cytosine Modification Profiles Define Epithelial-to-MesenChymal Cell-State Transitions. Epigenomics. 14(9). 519–535. 5 indexed citations

Wilkins, Owen M., et al.. (2022). S146L in MYC is a context-dependent activating substitution in cancer development. PLoS ONE. 17(8). e0272771–e0272771. 2 indexed citations

Moyer, Benjamin, Carol S. Ringelberg, Owen M. Wilkins, et al.. (2021). Kynurenine‐Induced Aryl Hydrocarbon Receptor Signaling in Mice Causes Body Mass Gain, Liver Steatosis, and Hyperglycemia. Obesity. 29(2). 337–349. 34 indexed citations

10.

Titus, Alexander, Lucas A. Salas, Owen M. Wilkins, et al.. (2020). Enrichment of CpG island shore region hypermethylation in epigenetic breast field cancerization. Epigenetics. 15(10). 1093–1106. 18 indexed citations

11.

Wilkins, Owen M., Kevin C. Johnson, E. Andrés Houseman, et al.. (2019). Genome-wide characterization of cytosine-specific 5-hydroxymethylation in normal breast tissue. Epigenetics. 15(4). 398–418. 11 indexed citations

12.

Feng, William W., Owen M. Wilkins, Scott Bang, et al.. (2019). CD36-Mediated Metabolic Rewiring of Breast Cancer Cells Promotes Resistance to HER2-Targeted Therapies. Cell Reports. 29(11). 3405–3420.e5. 150 indexed citations

13.

Herrmann, Katharine M. von, Lucas A. Salas, Alison L. Young, et al.. (2018). NLRP3 expression in mesencephalic neurons and characterization of a rare NLRP3 polymorphism associated with decreased risk of Parkinson’s disease. npj Parkinson s Disease. 4(1). 24–24. 144 indexed citations

14.

Wilkins, Owen M., Alexander Titus, Lucas A. Salas, et al.. (2018). MicroRNA-Related Genetic Variants Associated with Survival of Head and Neck Squamous Cell Carcinoma. Cancer Epidemiology Biomarkers & Prevention. 28(1). 127–136. 16 indexed citations

15.

Wilkins, Owen M., Zhe Sha, David A. Williams, et al.. (2017). Inhibition of the Proteasome β2 Site Sensitizes Triple-Negative Breast Cancer Cells to β5 Inhibitors and Suppresses Nrf1 Activation. Cell chemical biology. 24(2). 218–230. 90 indexed citations

16.

Wilkins, Owen M., Alexander Titus, Jiang Gui, et al.. (2017). Genome-scale identification of microRNA-related SNPs associated with risk of head and neck squamous cell carcinoma. Carcinogenesis. 38(10). 986–993. 17 indexed citations

17.

Canfield, Kaleigh, Jiaqi Li, Owen M. Wilkins, et al.. (2015). Receptor tyrosine kinase ERBB4 mediates acquired resistance to ERBB2 inhibitors in breast cancer cells. Cell Cycle. 14(4). 648–655. 60 indexed citations

18.

Wilkins, Owen M., Sondra L. Downey-Kopyscinski, David A. Williams, et al.. (2014). Cell-line-specific high background in the Proteasome-Glo assay of proteasome trypsin-like activity. Analytical Biochemistry. 451. 1–3. 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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