Daniel King

2.5k total citations · 1 hit paper
9 papers, 813 citations indexed

About

Daniel King is a scholar working on Molecular Biology, Genetics and Toxicology. According to data from OpenAlex, Daniel King has authored 9 papers receiving a total of 813 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Genetics and 1 paper in Toxicology. Recurrent topics in Daniel King's work include Genomics and Chromatin Dynamics (3 papers), Fungal and yeast genetics research (2 papers) and TGF-β signaling in diseases (2 papers). Daniel King is often cited by papers focused on Genomics and Chromatin Dynamics (3 papers), Fungal and yeast genetics research (2 papers) and TGF-β signaling in diseases (2 papers). Daniel King collaborates with scholars based in United States, Italy and Canada. Daniel King's co-authors include Anja Nohe, Beth Bragdon, Oleksandra Moseychuk, JoAnne Julian, Zhang Li, Kira Young, Nils O. Petersen, David W. Litchfield, Andrew A. Beharry and David L. Wilson and has published in prestigious journals such as Science, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Daniel King

9 papers receiving 798 citations

Hit Papers

Bone Morphogenetic Proteins: A critical review 2010 2026 2015 2020 2010 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel King United States 7 559 110 109 96 80 9 813
Carola Krause Germany 9 425 0.8× 78 0.7× 125 1.1× 114 1.2× 117 1.5× 13 711
Youlin Deng China 7 551 1.0× 97 0.9× 127 1.2× 90 0.9× 127 1.6× 12 940
Harumi Kawaki Japan 21 782 1.4× 101 0.9× 142 1.3× 106 1.1× 50 0.6× 58 1.1k
Azumi Hirata Japan 14 322 0.6× 76 0.7× 122 1.1× 108 1.1× 55 0.7× 40 579
Masaki Ishikawa Japan 18 789 1.4× 105 1.0× 202 1.9× 108 1.1× 76 0.9× 42 1.1k
Ronald L. Chandler United States 17 760 1.4× 177 1.6× 116 1.1× 129 1.3× 103 1.3× 33 1.2k
Ximeng Liu United States 11 593 1.1× 136 1.2× 122 1.1× 201 2.1× 90 1.1× 21 1.1k
Weiguang Wang United States 12 468 0.8× 108 1.0× 244 2.2× 64 0.7× 66 0.8× 14 753
Becky K. Brisson United States 19 467 0.8× 98 0.9× 109 1.0× 123 1.3× 146 1.8× 25 969
R. Gómez United States 15 371 0.7× 80 0.7× 189 1.7× 115 1.2× 90 1.1× 21 839

Countries citing papers authored by Daniel King

Since Specialization
Citations

This map shows the geographic impact of Daniel 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 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 King more than expected).

Fields of papers citing papers by Daniel King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel King

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

All Works

9 of 9 papers shown
1.
Poterba, Timothy, Christopher Vittal, Daniel King, et al.. (2024). The scalable variant call representation: enabling genetic analysis beyond one million genomes. Bioinformatics. 41(1). 1 indexed citations
2.
Lu, Wenhan, Laura D. Gauthier, Timothy Poterba, et al.. (2023). CHARR efficiently estimates contamination from DNA sequencing data. The American Journal of Human Genetics. 110(12). 2068–2076. 4 indexed citations
3.
Palmer, Duncan S., Wei Zhou, Liam Abbott, et al.. (2023). Analysis of genetic dominance in the UK Biobank. Science. 379(6639). 1341–1348. 23 indexed citations
4.
Auld, Douglas S., Debin Ji, Andrew A. Beharry, et al.. (2018). Potent and Selective Inhibitors of 8-Oxoguanine DNA Glycosylase. Journal of the American Chemical Society. 140(6). 2105–2114. 59 indexed citations
5.
Bragdon, Beth, Oleksandra Moseychuk, Daniel King, et al.. (2010). Casein Kinase 2 β-Subunit Is a Regulator of Bone Morphogenetic Protein 2 Signaling. Biophysical Journal. 99(3). 897–904. 55 indexed citations
6.
Bragdon, Beth, et al.. (2010). Bone Morphogenetic Proteins: A critical review. Cellular Signalling. 23(4). 609–620. 533 indexed citations breakdown →
7.
King, Daniel, et al.. (2006). Domain Structure and Protein Interactions of the Silent Information Regulator Sir3 Revealed by Screening a Nested Deletion Library of Protein Fragments. Journal of Biological Chemistry. 281(29). 20107–20119. 31 indexed citations
8.
King, Daniel, et al.. (1999). Structure of HAP1-18-DNA implicates direct allosteric effect of protein-DNA interactions on transcriptional activation.. Nature Structural Biology. 6(1). 22–27. 25 indexed citations
9.
King, Daniel, et al.. (1999). Structure of a HAP1-DNA complex reveals dramatically asymmetric DNA binding by a homodimeric protein.. Nature Structural Biology. 6(1). 64–71. 82 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

Rankless by CCL
2026