Daniel M. DeLaughter

4.0k total citations · 1 hit paper
17 papers, 860 citations indexed

About

Daniel M. DeLaughter is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Daniel M. DeLaughter has authored 17 papers receiving a total of 860 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 8 papers in Cardiology and Cardiovascular Medicine and 3 papers in Surgery. Recurrent topics in Daniel M. DeLaughter's work include Congenital heart defects research (7 papers), Single-cell and spatial transcriptomics (5 papers) and Cardiac Valve Diseases and Treatments (5 papers). Daniel M. DeLaughter is often cited by papers focused on Congenital heart defects research (7 papers), Single-cell and spatial transcriptomics (5 papers) and Cardiac Valve Diseases and Treatments (5 papers). Daniel M. DeLaughter collaborates with scholars based in United States, Germany and Switzerland. Daniel M. DeLaughter's co-authors include Christine E. Seidman, Jonathan G. Seidman, Joshua Gorham, Hiroko Wakimoto, Alexander G. Bick, Joey V. Barnett, William T. Pu, Jesse Gray, J. Travis Hinson and Jason Homsy and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Nature Medicine.

In The Last Decade

Daniel M. DeLaughter

16 papers receiving 854 citations

Hit Papers

Efficient in vivo genome editing prevents hypertrophic ca... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel M. DeLaughter United States 13 626 330 103 93 90 17 860
Vaibhao Janbandhu Australia 12 589 0.9× 302 0.9× 80 0.8× 109 1.2× 85 0.9× 17 942
Gaetano D’Amato United States 13 886 1.4× 304 0.9× 176 1.7× 127 1.4× 155 1.7× 17 1.1k
Cornelis J. Boogerd Netherlands 18 700 1.1× 365 1.1× 155 1.5× 55 0.6× 169 1.9× 26 1.0k
Calvin T. Hang United States 8 754 1.2× 159 0.5× 92 0.9× 128 1.4× 49 0.5× 12 863
Ching‐Pin Chang United States 12 593 0.9× 162 0.5× 54 0.5× 53 0.6× 57 0.6× 24 874
Manuel Rosa‐Garrido United States 16 740 1.2× 182 0.6× 32 0.3× 99 1.1× 46 0.5× 33 981
David E. Reese United States 11 536 0.9× 94 0.3× 68 0.7× 86 0.9× 126 1.4× 16 687
Eleanor Hilliard United States 12 356 0.6× 114 0.3× 46 0.4× 64 0.7× 81 0.9× 18 563
Hisham Alkhalidi Saudi Arabia 11 366 0.6× 95 0.3× 75 0.7× 71 0.8× 58 0.6× 50 650

Countries citing papers authored by Daniel M. DeLaughter

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. DeLaughter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel M. DeLaughter

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

All Works

17 of 17 papers shown
1.
Ward, Tarsha, Sarah U. Morton, Gabriela Venturini, et al.. (2025). Modeling SMAD2 Mutations in Induced Pluripotent Stem Cells Provides Insights Into Cardiovascular Disease Pathogenesis. Journal of the American Heart Association. 14(5). e036860–e036860. 2 indexed citations
2.
Chen, Jian, Xiaoran Zhang, Daniel M. DeLaughter, et al.. (2024). Molecular and Spatial Signatures of Mouse Embryonic Endothelial Cells at Single-Cell Resolution. Circulation Research. 134(5). 529–546. 16 indexed citations
3.
Ewoldt, Jourdan K., Micheal A. McLellan, Paige E. Cloonan, et al.. (2024). Hypertrophic cardiomyopathy–associated mutations drive stromal activation via EGFR-mediated paracrine signaling. Science Advances. 10(42). eadi6927–eadi6927. 6 indexed citations
4.
Reichart, Daniel, Gregory A. Newby, Hiroko Wakimoto, et al.. (2023). Efficient in vivo genome editing prevents hypertrophic cardiomyopathy in mice. Nature Medicine. 29(2). 412–421. 106 indexed citations breakdown →
5.
Zhang, Qi, Seong Won Kim, Joshua Gorham, et al.. (2022). Multiplexed Single‐Nucleus RNA Sequencing Using Lipid‐Oligo Barcodes. Current Protocols. 2(10). e579–e579. 1 indexed citations
6.
Nadelmann, Emily R., Joshua Gorham, Daniel Reichart, et al.. (2021). Isolation of Nuclei from Mammalian Cells and Tissues for Single‐Nucleus Molecular Profiling. Current Protocols. 1(5). e132–e132. 27 indexed citations
7.
DeLaughter, Daniel M.. (2018). The Use of the Fluidigm C1 for RNA Expression Analyses of Single Cells. Current Protocols in Molecular Biology. 122(1). e55–e55. 24 indexed citations
8.
Schlotter, Florian, Arda Halu, Shinji Goto, et al.. (2018). Spatiotemporal Multi-Omics Mapping Generates a Molecular Atlas of the Aortic Valve and Reveals Networks Driving Disease. Circulation. 138(4). 377–393. 167 indexed citations
9.
Schlotter, Florian, Arda Halu, Shinji Goto, et al.. (2018). Abstract 228: Multi-omics Mapping Generates a Molecular Atlas of the Aortic Valve and Reveals Networks Driving Disease. Arteriosclerosis Thrombosis and Vascular Biology. 38(Suppl_1).
10.
Bick, Alexander G., Hiroko Wakimoto, Kimberli J. Kamer, et al.. (2017). Cardiovascular homeostasis dependence on MICU2, a regulatory subunit of the mitochondrial calcium uniporter. Proceedings of the National Academy of Sciences. 114(43). E9096–E9104. 52 indexed citations
11.
DeLaughter, Daniel M., Danos C. Christodoulou, Christine E. Seidman, et al.. (2016). Transcriptional Profiling of Cultured, Embryonic Epicardial Cells Identifies Novel Genes and Signaling Pathways Regulated by TGFβR3 In Vitro. PLoS ONE. 11(8). e0159710–e0159710. 19 indexed citations
12.
DeLaughter, Daniel M., Alexander G. Bick, Hiroko Wakimoto, et al.. (2016). Single-Cell Resolution of Temporal Gene Expression during Heart Development. Developmental Cell. 39(4). 480–490. 300 indexed citations
13.
Sewell-Loftin, Mary Kathryn, Daniel M. DeLaughter, Christopher B. Brown, et al.. (2014). Myocardial contraction and hyaluronic acid mechanotransduction in epithelial-to-mesenchymal transformation of endocardial cells. Biomaterials. 35(9). 2809–2815. 17 indexed citations
14.
DeLaughter, Daniel M., Danos C. Christodoulou, Christine E. Seidman, et al.. (2013). Spatial transcriptional profile of the chick and mouse endocardial cushions identify novel regulators of endocardial EMT in vitro. Journal of Molecular and Cellular Cardiology. 59. 196–204. 33 indexed citations
15.
Townsend, Todd A., et al.. (2011). Endocardial cell epithelial-mesenchymal transformation requires Type III TGFβ receptor interaction with GIPC. Cellular Signalling. 24(1). 247–256. 26 indexed citations
16.
DeLaughter, Daniel M., et al.. (2011). What chick and mouse models have taught us about the role of the endocardium in congenital heart disease. Birth Defects Research Part A Clinical and Molecular Teratology. 91(6). 511–525. 31 indexed citations
17.
Townsend, Todd A., David Vaught, Daniel M. DeLaughter, et al.. (2010). Regulation of heart valve morphogenesis by Eph receptor ligand, ephrin‐A1. Developmental Dynamics. 239(12). 3226–3234. 33 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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