Daniel A. King

4.7k total citations
62 papers, 591 citations indexed

About

Daniel A. King is a scholar working on Oncology, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Daniel A. King has authored 62 papers receiving a total of 591 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Oncology, 11 papers in Genetics and 10 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Daniel A. King's work include Pancreatic and Hepatic Oncology Research (20 papers), Colorectal Cancer Screening and Detection (7 papers) and Cancer Genomics and Diagnostics (7 papers). Daniel A. King is often cited by papers focused on Pancreatic and Hepatic Oncology Research (20 papers), Colorectal Cancer Screening and Detection (7 papers) and Cancer Genomics and Diagnostics (7 papers). Daniel A. King collaborates with scholars based in United States, United Kingdom and China. Daniel A. King's co-authors include William D. O’Brien, Francis Cordova, Steven M. Scharf, Matthew E. Hurles, Tomas Fitzgerald, Pradeep Vasudevan, Alexander Haak, Diana Johnson, Sahar Mansour and Caroline J. Barelle and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Daniel A. King

51 papers receiving 554 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel A. King United States 13 149 142 85 80 72 62 591
Alicia Poplawski Germany 16 236 1.6× 101 0.7× 127 1.5× 121 1.5× 128 1.8× 52 752
Yuka Matsumoto Japan 15 110 0.7× 80 0.6× 22 0.3× 71 0.9× 59 0.8× 105 775
Kanwaldeep Singh Canada 14 222 1.5× 54 0.4× 32 0.4× 39 0.5× 90 1.3× 23 771
Eric Chau United States 14 166 1.1× 28 0.2× 84 1.0× 69 0.9× 225 3.1× 27 740
Song Peng China 16 154 1.0× 69 0.5× 92 1.1× 326 4.1× 51 0.7× 52 923
Anat Stein Israel 12 123 0.8× 30 0.2× 301 3.5× 57 0.7× 80 1.1× 19 692
Akira Yamaguchi Japan 16 228 1.5× 40 0.3× 29 0.3× 68 0.8× 110 1.5× 84 857
Takeshi UCHIYAMA Japan 13 182 1.2× 153 1.1× 16 0.2× 33 0.4× 41 0.6× 73 638
Elizabeth R. Davies United Kingdom 11 83 0.6× 96 0.7× 89 1.0× 109 1.4× 112 1.6× 25 532
Jean Cappello Australia 13 286 1.9× 50 0.4× 40 0.5× 52 0.7× 16 0.2× 26 819

Countries citing papers authored by Daniel A. King

Since Specialization
Citations

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

Fields of papers citing papers by Daniel A. King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel A. King

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel A. King. A scholar is included among the top collaborators of Daniel A. King 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 Daniel A. King. Daniel A. King 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.
Wu, Grace, Daniel A. King, Sepideh Gholami, et al.. (2025). Management of Peritoneal Metastasis in Patients with Pancreatic Ductal Adenocarcinoma. Current Oncology. 32(2). 103–103. 1 indexed citations
2.
Amini, Neda, Elliot Newman, Daniel A. King, et al.. (2024). Impact of postoperative pancreatic fistula on outcomes in pancreatoduodenectomy: a comprehensive analysis of American College of Surgeons National Surgical Quality Improvement Program data. Journal of Gastrointestinal Surgery. 28(9). 1406–1411. 4 indexed citations
3.
Knox, Jennifer J., Elizabeth M. Jaffee, Grainne M. O’Kane, et al.. (2024). Early results of the PASS-01 trial: Pancreatic adenocarcinoma signature stratification for treatment-01.. Journal of Clinical Oncology. 42(17_suppl). LBA4004–LBA4004. 6 indexed citations
4.
John, Kristen M., Cristina Valente, Amber N. Habowski, et al.. (2024). An AI-assisted navigation approach for patients with radiographic suspicion of new pancreas cancer.. Journal of Clinical Oncology. 42(16_suppl). 11002–11002. 1 indexed citations
5.
Amini, Neda, et al.. (2024). ctDNA for clinical decision support in pancreatic cancer.. Journal of Clinical Oncology. 42(16_suppl). e16354–e16354. 1 indexed citations
6.
Newman, Elliot, et al.. (2024). 369 IDEAL OUTCOME POST-PANCREATODUODENECTOMY: A COMPREHENSIVE HEALTHCARE SYSTEM ANALYSIS. Gastroenterology. 166(5). S–1792. 1 indexed citations
7.
Newman, Elliot, Daniel A. King, Danielle K. DePeralta, et al.. (2024). Ideal outcome post-pancreatoduodenectomy: a comprehensive healthcare system analysis. Langenbeck s Archives of Surgery. 409(1). 339–339. 1 indexed citations
8.
Carey, Caitlin E., Rebecca Shafee, Robbee Wedow, et al.. (2024). Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation. Nature Human Behaviour. 8(8). 1599–1615. 8 indexed citations
9.
King, Daniel A., et al.. (2023). Therapeutic Implications of Oncogenic Missense HER2 (ERBB2) Mutations in Gastric Adenocarcinoma. JCO Precision Oncology. 7(7). e2200093–e2200093. 2 indexed citations
10.
Yao, Min, Jonathan Preall, Johannes T.‐H. Yeh, et al.. (2023). Plasma cells in human pancreatic ductal adenocarcinoma secrete antibodies against self-antigens. JCI Insight. 8(21). 6 indexed citations
11.
12.
King, Daniel A., et al.. (2022). Immunotherapy in the Management of Esophagogastric Cancer: A Practical Review. JCO Oncology Practice. 19(3). 107–115. 8 indexed citations
13.
Wang, James, Brett Z. Fite, Aris J. Kare, et al.. (2022). Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer. Theranostics. 12(18). 7884–7902. 5 indexed citations
14.
Huang, Jie, Zhisheng Liang, Janice M. Ranson, et al.. (2021). PAGEANT: personal access to genome and analysis of natural traits. Nucleic Acids Research. 50(7). e39–e39.
15.
Zhou, Zhenwei, Jia Wen, Yun Li, et al.. (2021). Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study. Frontiers in Genetics. 12. 669441–669441. 9 indexed citations
16.
King, Daniel A., et al.. (2020). Marked Decrease in CA 19-9 Level Belies Rapidly Progressive Lymphangitic Carcinomatosis in a Case of Metastatic Pancreatic Cancer. SHILAP Revista de lepidopterología. 6(1). 102–106.
17.
King, Daniel A., Alejandro Sifrim, Tomas Fitzgerald, et al.. (2017). Detection of structural mosaicism from targeted and whole-genome sequencing data. Genome Research. 27(10). 1704–1714. 38 indexed citations
18.
Carvalho, Claudia M.B., Rolph Pfundt, Daniel A. King, et al.. (2015). Absence of Heterozygosity Due to Template Switching during Replicative Rearrangements. The American Journal of Human Genetics. 96(4). 555–564. 42 indexed citations
19.
Schideman, Lance, et al.. (2014). Algal cell disruption using microbubbles to localize ultrasonic energy. Bioresource Technology. 173. 448–451. 16 indexed citations
20.
King, Daniel A.. (2012). Collapse dynamics of ultrasound contrast agent microbubbles. PhDT. 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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