Stephen Horrigan

1.1k total citations
42 papers, 817 citations indexed

About

Stephen Horrigan is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Stephen Horrigan has authored 42 papers receiving a total of 817 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 15 papers in Hematology and 10 papers in Oncology. Recurrent topics in Stephen Horrigan's work include Acute Myeloid Leukemia Research (11 papers), Cancer-related gene regulation (7 papers) and Ubiquitin and proteasome pathways (5 papers). Stephen Horrigan is often cited by papers focused on Acute Myeloid Leukemia Research (11 papers), Cancer-related gene regulation (7 papers) and Ubiquitin and proteasome pathways (5 papers). Stephen Horrigan collaborates with scholars based in United States, Australia and United Kingdom. Stephen Horrigan's co-authors include Carol A. Westbrook, Zarema Arbieva, Noreen Fulton, Celeste B. Rich, Ronald Hoffman, Z. Li, Barbara W. Streeten, J.A. Foster, Kapil N. Bhalla and Seby Edassery and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Blood.

In The Last Decade

Stephen Horrigan

37 papers receiving 796 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Horrigan United States 17 559 203 147 138 95 42 817
Anna Kilbey United Kingdom 17 647 1.2× 249 1.2× 217 1.5× 122 0.9× 82 0.9× 35 891
Evangelia Loizou United States 7 548 1.0× 148 0.7× 243 1.7× 75 0.5× 118 1.2× 8 775
Lalitha Nagarajan United States 20 690 1.2× 267 1.3× 177 1.2× 175 1.3× 109 1.1× 46 1.0k
Ettore Meccia Italy 12 616 1.1× 104 0.5× 152 1.0× 90 0.7× 133 1.4× 18 837
Philip Vlummens Belgium 13 323 0.6× 137 0.7× 124 0.8× 99 0.7× 78 0.8× 33 503
Mareike Roth Austria 10 637 1.1× 190 0.9× 149 1.0× 63 0.5× 160 1.7× 16 909
Shannon M. Buckley United States 13 598 1.1× 141 0.7× 165 1.1× 73 0.5× 71 0.7× 19 770
Silvia Álvarez United States 7 747 1.3× 207 1.0× 254 1.7× 88 0.6× 95 1.0× 8 967
Hyung C. Suh United States 13 383 0.7× 186 0.9× 178 1.2× 78 0.6× 58 0.6× 44 636
Matthew Malehorn United States 4 543 1.0× 348 1.7× 404 2.7× 103 0.7× 122 1.3× 6 896

Countries citing papers authored by Stephen Horrigan

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Horrigan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Horrigan

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Horrigan. A scholar is included among the top collaborators of Stephen Horrigan 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 Stephen Horrigan. Stephen Horrigan 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.
Zhou, Yuanping, et al.. (2025). Replication-driven HBV cccDNA loss in chimeric mice with humanized livers. Journal of Virology. 99(11). e0129525–e0129525.
2.
Wei, Lai, Wenxian Yang, Stephen Horrigan, et al.. (2024). P3.12D.01 A Phase Ib Study of Osimertinib and Tegavivint as First-Line Therapy in Patients with Metastatic EGFR-Mutant Non-Small Cell Lung Cancer (NSCLC). Journal of Thoracic Oncology. 19(10). S346–S346.
3.
Birdwell, Christine, Warren Fiskus, Tapan M. Kadia, et al.. (2023). Preclinical efficacy of targeting epigenetic mechanisms in AML with 3q26 lesions and EVI1 overexpression. Leukemia. 38(3). 545–556. 5 indexed citations
4.
Braggio, Danielle, Feng Jin, Abeba Zewdu, et al.. (2022). Preclinical efficacy of the Wnt/β-catenin pathway inhibitor BC2059 for the treatment of desmoid tumors. PLoS ONE. 17(10). e0276047–e0276047. 12 indexed citations
5.
Raleigh, Michael D., Nicola Beltraminelli, Mark LeSage, et al.. (2021). Attenuating nicotine’s effects with high affinity human anti-nicotine monoclonal antibodies. PLoS ONE. 16(7). e0254247–e0254247. 5 indexed citations
6.
Soldi, Raffaella, Tithi Ghosh, Hariprasad Vankayalapati, et al.. (2021). The Small Molecule BC-2059 Inhibits Wingless/Integrated (Wnt)-Dependent Gene Transcription in Cancer through Disruption of the Transducin β-Like 1-β-Catenin Protein Complex. Journal of Pharmacology and Experimental Therapeutics. 378(2). 77–86. 11 indexed citations
7.
Thisted, Thomas, Céline Walmacq, Everett Stone, et al.. (2019). Optimization of a nicotine degrading enzyme for potential use in treatment of nicotine addiction. BMC Biotechnology. 19(1). 56–56. 18 indexed citations
8.
Pentel, Paul R., Michael D. Raleigh, Mark LeSage, et al.. (2018). The nicotine-degrading enzyme NicA2 reduces nicotine levels in blood, nicotine distribution to brain, and nicotine discrimination and reinforcement in rats. BMC Biotechnology. 18(1). 46–46. 13 indexed citations
9.
Khong, Tiffany, et al.. (2017). β-Catenin Inhibitor BC2059 Is Efficacious as Monotherapy or in Combination with Proteasome Inhibitor Bortezomib in Multiple Myeloma. Molecular Cancer Therapeutics. 16(9). 1765–1778. 39 indexed citations
10.
Fiskus, Warren, S. Sharma, Saikat Saha, et al.. (2014). Pre-clinical efficacy of combined therapy with novel β-catenin antagonist BC2059 and histone deacetylase inhibitor against AML cells. Leukemia. 29(6). 1267–1278. 82 indexed citations
11.
Chen, Bo, Ricardo Cibotti, Brian Naiman, et al.. (2008). Genomic-Based High Throughput Screening Identifies Small Molecules That Differentially Inhibit the Antiviral and Immunomodulatory Effects of IFN-α. Molecular Medicine. 14(7-8). 374–382. 3 indexed citations
12.
Hu, Zhenbo, Ignatius Gomes, Stephen Horrigan, et al.. (2001). A novel nuclear protein, 5qNCA (LOC51780) is a candidate for the myeloid leukemia tumor suppressor gene on chromosome 5 band q31. Oncogene. 20(47). 6946–6954. 62 indexed citations
13.
Arbieva, Zarema, et al.. (2000). High-Resolution Physical Map and Transcript Identification of a Prostate Cancer Deletion Interval on 8p22. Genome Research. 10(2). 244–257. 27 indexed citations
14.
Westbrook, Carol A., et al.. (2000). Novel nuclear receptor coactivator is a candidate for the del(5q) Leukemia tumor suppressor gene. Experimental Hematology. 28(12). 1492–1492. 2 indexed citations
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17.
Bartoloni, Lucia, Stephen Horrigan, Kristi D. Viles, et al.. (1998). Use of a CEPH Meiotic Breakpoint Panel to Refine the Locus of Limb-Girdle Muscular Dystrophy Type 1A (LGMD1A) to a 2-Mb Interval on 5q31. Genomics. 54(2). 250–255. 18 indexed citations
18.
19.
Zeremski, Marija, Stephen Horrigan, Irina A. Grigorian, Carol A. Westbrook, & Andrei V. Gudkov. (1997). Localization of the candidate tumor suppressor geneING1 to human chromosome 13q34. Somatic Cell and Molecular Genetics. 23(3). 233–236. 35 indexed citations
20.
Lyons, Gary E., et al.. (1994). Protooncogene c‐ski is expressed in both proliferating and postmitotic neuronal populations. Developmental Dynamics. 201(4). 354–365. 43 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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