Emma Dyer

1.6k total citations · 1 hit paper
23 papers, 726 citations indexed

About

Emma Dyer is a scholar working on Cardiology and Cardiovascular Medicine, Genetics and Molecular Biology. According to data from OpenAlex, Emma Dyer has authored 23 papers receiving a total of 726 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cardiology and Cardiovascular Medicine, 7 papers in Genetics and 6 papers in Molecular Biology. Recurrent topics in Emma Dyer's work include Cardiomyopathy and Myosin Studies (7 papers), Cardiovascular Effects of Exercise (5 papers) and Inflammatory Bowel Disease (5 papers). Emma Dyer is often cited by papers focused on Cardiomyopathy and Myosin Studies (7 papers), Cardiovascular Effects of Exercise (5 papers) and Inflammatory Bowel Disease (5 papers). Emma Dyer collaborates with scholars based in United States, United Kingdom and Australia. Emma Dyer's co-authors include Alexander T. Pearson, Frederick M. Howard, Siddhi Ramesh, Catherine A. Gao, Yuan Luo, Nikolay S. Markov, David T. Rubin, Steven B. Marston, Dominic J. Wells and Benjamin D. McDonald and has published in prestigious journals such as Journal of Biological Chemistry, Nature Medicine and Gastroenterology.

In The Last Decade

Emma Dyer

22 papers receiving 710 citations

Hit Papers

Comparing scientific abstracts generated by ChatGPT to re... 2023 2026 2024 2025 2023 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emma Dyer United States 11 299 190 162 134 132 23 726
T. Beck United States 9 85 0.3× 85 0.4× 38 0.2× 46 0.3× 221 1.7× 12 566
Frederick M. Howard United States 16 356 1.2× 373 2.0× 14 0.1× 369 2.8× 137 1.0× 52 1.3k
Nikolay S. Markov United States 8 286 1.0× 156 0.8× 13 0.1× 112 0.8× 156 1.2× 15 842
Zunamys I. Carrero Germany 12 310 1.0× 257 1.4× 16 0.1× 184 1.4× 285 2.2× 23 860
Christine M. Cutillo United States 7 90 0.3× 91 0.5× 18 0.1× 36 0.3× 118 0.9× 7 504
Hannah Sophie Muti Germany 9 297 1.0× 267 1.4× 12 0.1× 223 1.7× 59 0.4× 15 647
Dominic Amara United States 11 106 0.4× 41 0.2× 16 0.1× 66 0.5× 84 0.6× 32 574
David Ziyou Chen Singapore 13 211 0.7× 96 0.5× 20 0.1× 341 2.5× 168 1.3× 36 764
Ugljesa Djuric Canada 19 156 0.5× 242 1.3× 14 0.1× 222 1.7× 746 5.7× 24 1.5k
D Hafler United States 8 48 0.2× 68 0.4× 20 0.1× 74 0.6× 132 1.0× 9 1.1k

Countries citing papers authored by Emma Dyer

Since Specialization
Citations

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

Fields of papers citing papers by Emma Dyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emma Dyer

This figure shows the co-authorship network connecting the top 25 collaborators of Emma Dyer. A scholar is included among the top collaborators of Emma Dyer 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 Emma Dyer. Emma Dyer 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.
Dolezal, James M., Sara Kochanny, Emma Dyer, et al.. (2024). Slideflow: deep learning for digital histopathology with real-time whole-slide visualization. BMC Bioinformatics. 25(1). 134–134. 20 indexed citations
3.
Dolezal, James M., Emma Dyer, Sara Kochanny, et al.. (2024). Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning. EBioMedicine. 107. 105276–105276. 5 indexed citations
4.
Frisbie, Leonard, Emma Dyer, Claudette M. St. Croix, et al.. (2024). Carcinoma-associated mesenchymal stem cells promote ovarian cancer heterogeneity and metastasis through mitochondrial transfer. Cell Reports. 43(8). 114551–114551. 19 indexed citations
5.
Vaidya, Anurag, Richard J. Chen, Drew F. K. Williamson, et al.. (2024). Demographic bias in misdiagnosis by computational pathology models. Nature Medicine. 30(4). 1174–1190. 39 indexed citations
6.
Gao, Catherine A., Frederick M. Howard, Nikolay S. Markov, et al.. (2023). Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers. npj Digital Medicine. 6(1). 75–75. 373 indexed citations breakdown →
7.
Garcia, Nicole, et al.. (2022). Factors Associated With Fecal Calprotectin Sample Collection Compliance: An IBD Center Quality Improvement Project. Crohn s & Colitis 360. 4(4). otac042–otac042. 2 indexed citations
9.
McDonald, Benjamin D., Emma Dyer, & David T. Rubin. (2022). IL-23 Monoclonal Antibodies for IBD: So Many, So Different?. Journal of Crohn s and Colitis. 16(Supplement_2). ii42–ii53. 23 indexed citations
10.
Dyer, Emma, et al.. (2020). FmhA and FmhC of Staphylococcus aureus incorporate serine residues into peptidoglycan cross-bridges. Journal of Biological Chemistry. 295(39). 13664–13676. 20 indexed citations
11.
Marston, Steven B., Adam Jacques, Emma Dyer, et al.. (2020). Donor hearts in the Sydney Heart Bank: reliable control but is it ‘normal’ heart?. Biophysical Reviews. 12(4). 799–803. 1 indexed citations
12.
Song, Weihua, Emma Dyer, Daniel J. Stuckey, et al.. (2011). Molecular Mechanism of the E99K Mutation in Cardiac Actin (ACTC Gene) That Causes Apical Hypertrophy in Man and Mouse. Journal of Biological Chemistry. 286(31). 27582–27593. 51 indexed citations
13.
Song, Weihua, Emma Dyer, Daniel J. Stuckey, et al.. (2010). Investigation of a transgenic mouse model of familial dilated cardiomyopathy. Journal of Molecular and Cellular Cardiology. 49(3). 380–389. 51 indexed citations
14.
Smith, Lee B., Patrick W. F. Hadoke, Emma Dyer, et al.. (2010). Haploinsufficiency of the murine Col3a1 locus causes aortic dissection: a novel model of the vascular type of Ehlers–Danlos syndrome. Cardiovascular Research. 90(1). 182–190. 52 indexed citations
15.
Song, Wan, Daniel J. Stuckey, Emma Dyer, et al.. (2009). Mouse HCM Model Expression E99K ACTC Mutation Reproduces the Clinical HCM Phenotype. The Journal of General Physiology. 134. 1 indexed citations
16.
Song, Weihua, Daniel J. Stuckey, Emma Dyer, et al.. (2009). Mouse HCM Model Expressing E99K ACTC Mutation Reproduces Phenotypes As Found In Human Patients. Biophysical Journal. 96(3). 499a–500a. 2 indexed citations
17.
Dyer, Emma, Weihua Song, Dominic J. Wells, & Steven B. Marston. (2008). Functional investigation of a transgenic mouse model of apical HCM with ACTC E99K mutation. Journal of Molecular and Cellular Cardiology. 44(4). 730–730. 2 indexed citations
18.
Dyer, Emma, et al.. (2008). Functional effects of DCM mutation G159D in troponin C from an explanted heart. Journal of Molecular and Cellular Cardiology. 44(4). 729–730. 2 indexed citations
19.
Song, Weihua, Emma Dyer, Dominic J. Wells, et al.. (2008). Investigation of a mouse model of familial DCM with ACTC E361G mutation. Journal of Molecular and Cellular Cardiology. 44(4). 820–821. 1 indexed citations
20.
Dyer, Emma, et al.. (2007). In vitro motility studies of HCM and DCM mutations in cardiac muscle actin. Biophysical Journal. 1 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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