Jay A. Moore

536 total citations · 1 hit paper
14 papers, 166 citations indexed

About

Jay A. Moore is a scholar working on Cancer Research, Oncology and Surgery. According to data from OpenAlex, Jay A. Moore has authored 14 papers receiving a total of 166 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cancer Research, 9 papers in Oncology and 5 papers in Surgery. Recurrent topics in Jay A. Moore's work include Cancer Genomics and Diagnostics (9 papers), Pancreatic and Hepatic Oncology Research (4 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers). Jay A. Moore is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Pancreatic and Hepatic Oncology Research (4 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers). Jay A. Moore collaborates with scholars based in United States, Japan and Switzerland. Jay A. Moore's co-authors include Garrett M. Frampton, Justin Y. Newberg, Radwa Sharaf, Smruthy Sivakumar, Douglas I. Lin, Ericka M. Ebot, Caterina I. Colón, Julien Sage, Afshin Dowlati and Christine M. Lovly and has published in prestigious journals such as Journal of Clinical Oncology, Blood and JNCI Journal of the National Cancer Institute.

In The Last Decade

Jay A. Moore

12 papers receiving 165 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Integrative Analysis of a Large Real-World Cohort of Small Cell Lung Cancer Identifies Distinct Genetic Subtypes and Insights into Histologic Transformation

2023 75 citations Smruthy Sivakumar, Jay A. Moore et al. Cancer Discovery profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jay A. Moore United States	7	116	75	51	49	36	14	166
Abirami Sivapiragasam United States	8	107 0.9×	37 0.5×	40 0.8×	19 0.4×	41 1.1×	33	178
Laia Serrano Spain	7	55 0.5×	48 0.6×	73 1.4×	23 0.5×	64 1.8×	9	156
Masayuki Shirasawa Japan	10	167 1.4×	27 0.4×	108 2.1×	47 1.0×	21 0.6×	25	213
Justin Harold United States	8	73 0.6×	48 0.6×	30 0.6×	32 0.7×	37 1.0×	18	186
Annick Chevalier-Place France	6	56 0.5×	33 0.4×	48 0.9×	26 0.5×	15 0.4×	7	148
Jee‐Soo Lee South Korea	6	62 0.5×	64 0.9×	30 0.6×	13 0.3×	60 1.7×	24	164
Erik Asmus United States	6	100 0.9×	39 0.5×	41 0.8×	12 0.2×	36 1.0×	9	179
Yang Ma China	8	79 0.7×	167 2.2×	45 0.9×	22 0.4×	75 2.1×	17	221
Nicole C.M. Visser Netherlands	9	41 0.4×	43 0.6×	27 0.5×	41 0.8×	46 1.3×	20	317
Nigel Biswas–Baldwin United Kingdom	5	140 1.2×	85 1.1×	124 2.4×	27 0.6×	31 0.9×	9	252

Countries citing papers authored by Jay A. Moore

Since Specialization

Citations

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

Fields of papers citing papers by Jay A. Moore

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay A. Moore. 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 Jay A. Moore. The network helps show where Jay A. Moore may publish in the future.

Co-authorship network of co-authors of Jay A. Moore

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

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

Wijetunga, N. Ari, Krishna Kanchi, Jay A. Moore, et al.. (2024). Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features. Cancer Research Communications. 4(9). 2320–2334. 3 indexed citations

Yamamoto, Hiroyuki, Hiroyuki Arai, Ritsuko Oikawa, et al.. (2024). The Molecular Landscape of Gastric Cancers for Novel Targeted Therapies from Real-World Genomic Profiling. Targeted Oncology. 19(3). 459–471.

Takeda, Hiroyuki, Hiroyuki Yamamoto, Ritsuko Oikawa, et al.. (2024). Genomic Profiling of Small Intestine Cancers From a Real-World Data Set Identifies Subgroups With Actionable Alterations. JCO Precision Oncology. 8(8). e2300425–e2300425.

Sivakumar, Smruthy, Jay A. Moore, Meagan Montesion, et al.. (2023). Integrative Analysis of a Large Real-World Cohort of Small Cell Lung Cancer Identifies Distinct Genetic Subtypes and Insights into Histologic Transformation. Cancer Discovery. 13(7). 1572–1591. 75 indexed citations breakdown →

Moore, Jay A., Russell W. Madison, Justin Y. Newberg, et al.. (2023). Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response. JCO Precision Oncology. 7(7). e2300093–e2300093. 13 indexed citations

Madison, Russell W., Jay A. Moore, Dexter X. Jin, et al.. (2023). A Novel HRD Signature Is Predictive of FOLFIRINOX Benefit in Metastatic Pancreatic Cancer. The Oncologist. 28(8). 691–698. 11 indexed citations

Sivakumar, Smruthy, Jessica Lee, Jay A. Moore, et al.. (2023). Comprehensive genomic profiling and treatment patterns across ancestries in advanced prostate cancer: a large-scale retrospective analysis. The Lancet Digital Health. 5(6). e380–e389. 5 indexed citations

Umemoto, Kumiko, Hiroyuki Yamamoto, Ritsuko Oikawa, et al.. (2022). The Molecular Landscape of Pancreatobiliary Cancers for Novel Targeted Therapies From Real-World Genomic Profiling. JNCI Journal of the National Cancer Institute. 114(9). 1279–1286. 14 indexed citations

Murugesan, Karthikeyan, Radwa Sharaf, Meagan Montesion, et al.. (2021). Genomic Profiling of Combined Hepatocellular Cholangiocarcinoma Reveals Genomics Similar to Either Hepatocellular Carcinoma or Cholangiocarcinoma. JCO Precision Oncology. 5(5). 1285–1296. 12 indexed citations

10.

Sivakumar, Smruthy, Jay A. Moore, Julia F. Hopkins, et al.. (2021). Ancestral characterization of the genomic landscape, comprehensive genomic profiling utilization, and treatment patterns may inform disparities in advanced prostate cancer: A large-scale analysis.. Journal of Clinical Oncology. 39(15_suppl). 5003–5003. 7 indexed citations

11.

Trabucco, Sally E., Ethan Sokol, Sophia L. Maund, et al.. (2021). Prediction and Characterization of Diffuse Large B-Cell Lymphoma Cell-of-Origin Subtypes Using Targeted Sequencing. Future Oncology. 17(31). 4171–4183. 3 indexed citations

12.

Umemoto, Kumiko, Hiroyuki Yamamoto, Ritsuko Oikawa, et al.. (2021). Genomic alterations for novel targeted therapies in pancreatobiliary cancers from real-world data.. Journal of Clinical Oncology. 39(15_suppl). 4124–4124. 2 indexed citations

13.

Trabucco, Sally E., Ethan Sokol, Jay A. Moore, et al.. (2018). Prediction and Characterization of Diffuse Large B-Cell Lymphoma (DLBCL) Cell of Origin (COO) Subtypes Using Genomic Features from Targeted Next-Generation Sequencing. Blood. 132(Supplement 1). 1561–1561. 1 indexed citations

14.

Gessler, Manfred, et al.. (1993). Homozygous inactivation of WTI in a Wilms' tumor associated with the WAGR syndrome. Genes Chromosomes and Cancer. 7(3). 131–136. 20 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.

Explore authors with similar magnitude of impact