Kyle J. Gaulton

16.2k total citations · 3 hit papers
44 papers, 3.0k citations indexed

About

Kyle J. Gaulton is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Kyle J. Gaulton has authored 44 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 26 papers in Genetics and 20 papers in Surgery. Recurrent topics in Kyle J. Gaulton's work include Pancreatic function and diabetes (19 papers), Genetic Associations and Epidemiology (13 papers) and Epigenetics and DNA Methylation (12 papers). Kyle J. Gaulton is often cited by papers focused on Pancreatic function and diabetes (19 papers), Genetic Associations and Epidemiology (13 papers) and Epigenetics and DNA Methylation (12 papers). Kyle J. Gaulton collaborates with scholars based in United States, United Kingdom and Belgium. Kyle J. Gaulton's co-authors include Sebastian Preißl, Joshua Chiou, Bing Ren, Mark I. McCarthy, Karen L. Mohlke, Jorge Ferrer, Michael Miller, Marie P. Fogarty, Yunjiang Qiu and Mei-Lin Okino and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Kyle J. Gaulton

42 papers receiving 3.0k citations

Hit Papers

Type 2 diabetes genetic loci informed by multi-trait asso... 2018 2026 2020 2023 2018 2021 2021 100 200 300

Peers

Kyle J. Gaulton
Karen L. Mohlke United States
Chun‐Fang Xu United Kingdom
Nathan O. Stitziel United States
Daniel M. Jordan United States
Joshua Chiou United States
Danielle Welter Luxembourg
Joannella Morales United States
Peggy Hall United States
Alexandra C. Nica Switzerland
Karen L. Mohlke United States
Kyle J. Gaulton
Citations per year, relative to Kyle J. Gaulton Kyle J. Gaulton (= 1×) peers Karen L. Mohlke

Countries citing papers authored by Kyle J. Gaulton

Since Specialization
Citations

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

Fields of papers citing papers by Kyle J. Gaulton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyle J. Gaulton. 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 Kyle J. Gaulton. The network helps show where Kyle J. Gaulton may publish in the future.

Co-authorship network of co-authors of Kyle J. Gaulton

This figure shows the co-authorship network connecting the top 25 collaborators of Kyle J. Gaulton. A scholar is included among the top collaborators of Kyle J. Gaulton 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 Kyle J. Gaulton. Kyle J. Gaulton 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.
Chiou, Joshua, et al.. (2024). Genetic Discovery and Risk Prediction for Type 1 Diabetes in Individuals Without High-Risk HLA-DR3/DR4 Haplotypes. Diabetes Care. 48(2). 202–211. 6 indexed citations
2.
Smith, Kirk, Aaron J. Deutsch, Sarah Hsu, et al.. (2024). Multi-ancestry polygenic mechanisms of type 2 diabetes. Nature Medicine. 30(4). 1065–1074. 39 indexed citations
3.
Xu, Le, Chunting Tan, Justinn Barr, et al.. (2024). Context-dependent roles of mitochondrial LONP1 in orchestrating the balance between airway progenitor versus progeny cells. Cell stem cell. 31(10). 1465–1483.e6. 3 indexed citations
4.
Robertson, Catherine C., Peter Arvan, Shuibing Chen, et al.. (2024). Untangling the genetics of beta cell dysfunction and death in type 1 diabetes. Molecular Metabolism. 86. 101973–101973. 4 indexed citations
5.
Westerman, Kenneth E., Kirk Smith, Joshua Chiou, et al.. (2022). High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease. Diabetologia. 66(3). 495–507. 31 indexed citations
6.
Preißl, Sebastian, Kyle J. Gaulton, & Bing Ren. (2022). Characterizing cis-regulatory elements using single-cell epigenomics. Nature Reviews Genetics. 24(1). 21–43. 124 indexed citations
7.
Yan, Jian, Yunjiang Qiu, Yimeng Yin, et al.. (2021). Systematic analysis of binding of transcription factors to noncoding variants. Nature. 591(7848). 147–151. 88 indexed citations
8.
Geusz, Ryan J., Allen Wang, Joshua Chiou, et al.. (2021). Pancreatic progenitor epigenome maps prioritize type 2 diabetes risk genes with roles in development. eLife. 10. 14 indexed citations
9.
Aylward, Anthony, Mei-Lin Okino, Paola Benaglio, et al.. (2021). Glucocorticoid signaling in pancreatic islets modulates gene regulatory programs and genetic risk of type 2 diabetes. PLoS Genetics. 17(5). e1009531–e1009531. 18 indexed citations
10.
Chiou, Joshua, Ryan J. Geusz, Mei-Lin Okino, et al.. (2021). Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature. 594(7863). 398–402. 205 indexed citations breakdown →
11.
Chiou, Joshua, Chun Zeng, Cheng Zhang, et al.. (2021). Single-cell chromatin accessibility identifies pancreatic islet cell type– and state-specific regulatory programs of diabetes risk. Nature Genetics. 53(4). 455–466. 89 indexed citations
12.
Benaglio, Paola, Agnieszka D’Antonio‐Chronowska, Wubin Ma, et al.. (2019). Allele-specific NKX2-5 binding underlies multiple genetic associations with human electrocardiographic traits. Nature Genetics. 51(10). 1506–1517. 30 indexed citations
13.
Gaulton, Kyle J.. (2017). Mechanisms of Type 2 Diabetes Risk Loci. Current Diabetes Reports. 17(9). 72–72. 30 indexed citations
14.
Field, Yair, Evan A. Boyle, Natalie Telis, et al.. (2016). Detection of human adaptation during the past 2000 years. Science. 354(6313). 760–764. 233 indexed citations
15.
Bunt, Martijn van de, Jocelyn E. Manning Fox, Xiao-Qing Dai, et al.. (2015). Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors. PLoS Genetics. 11(12). e1005694–e1005694. 105 indexed citations
16.
Reschen, Michael E., Kyle J. Gaulton, Da Lin, et al.. (2015). Lipid-Induced Epigenomic Changes in Human Macrophages Identify a Coronary Artery Disease-Associated Variant that Regulates PPAP2B Expression through Altered C/EBP-Beta Binding. PLoS Genetics. 11(4). e1005061–e1005061. 58 indexed citations
17.
McCarthy, Davis J., Peter Humburg, Alexander Kanapin, et al.. (2014). Choice of transcripts and software has a large effect on variant annotation. Genome Medicine. 6(3). 26–26. 128 indexed citations
18.
Fogarty, Marie P., Maren E. Cannon, Swarooparani Vadlamudi, Kyle J. Gaulton, & Karen L. Mohlke. (2014). Identification of a Regulatory Variant That Binds FOXA1 and FOXA2 at the CDC123/CAMK1D Type 2 Diabetes GWAS Locus. PLoS Genetics. 10(9). e1004633–e1004633. 50 indexed citations
19.
Bunt, Martijn van de, Kyle J. Gaulton, Leopold Parts, et al.. (2013). The miRNA Profile of Human Pancreatic Islets and Beta-Cells and Relationship to Type 2 Diabetes Pathogenesis. PLoS ONE. 8(1). e55272–e55272. 156 indexed citations
20.
Gaulton, Kyle J., Takao Nammo, Lorenzo Pasquali, et al.. (2010). A map of open chromatin in human pancreatic islets. Nature Genetics. 42(3). 255–259. 390 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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