David J. Connolly

2.1k total citations · 1 hit paper
56 papers, 1.5k citations indexed

About

David J. Connolly is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, David J. Connolly has authored 56 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Cardiology and Cardiovascular Medicine, 32 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Molecular Biology. Recurrent topics in David J. Connolly's work include Cardiovascular Conditions and Treatments (31 papers), Cardiomyopathy and Myosin Studies (16 papers) and Cardiac Arrhythmias and Treatments (9 papers). David J. Connolly is often cited by papers focused on Cardiovascular Conditions and Treatments (31 papers), Cardiomyopathy and Myosin Studies (16 papers) and Cardiac Arrhythmias and Treatments (9 papers). David J. Connolly collaborates with scholars based in United Kingdom, Ireland and United States. David J. Connolly's co-authors include Patrick J. Guiry, Timothy P. O’Sullivan, Virginia Luis Fuentes, Adrian Boswood, Jayesh Dudhia, Mary E. McCarthy, Cormac P. Saunders, Harriet M. Syme, Kieran Borgeat and Florien Jenner and has published in prestigious journals such as PLoS ONE, Scientific Reports and Biophysical Journal.

In The Last Decade

David J. Connolly

53 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Synthesis of quinazolinones and quinazolines

2005 545 citations David J. Connolly et al. profile →

Peers

David J. Connolly

RNMI

CCM

EPIDE

E. Yiannaki Greece

George Makris Greece

Eun Sil Park South Korea

Jiaxi Chen China

Hyun Il Lee South Korea

Jianwen Guo China

Zhuang Jin China

Gilad Halpert Israel

Giuseppe Palazzo Italy

Wen Guo China

E. Yiannaki Greece

David J. Connolly

90 ×0.1

168 ×0.4

73 ×0.2

RNMI

47 ×0.1

CCM

77 ×0.5

EPIDE

Citations per year, relative to David J. Connolly David J. Connolly (= 1×) peers E. Yiannaki

Countries citing papers authored by David J. Connolly

Since Specialization

Citations

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

Fields of papers citing papers by David J. Connolly

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David J. Connolly

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

All Works

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20 of 20 papers shown

Bargary, Norma, et al.. (2026). Predicting functional results of percutaneous coronary intervention using machine learning modelling. International Journal of Cardiology. 449. 134183–134183.

Fezzi, Simone, Norma Bargary, Daixin Ding, et al.. (2025). Validation of machine learning angiography-derived physiological pattern of coronary artery disease. European Heart Journal - Digital Health. 6(4). 577–586. 2 indexed citations

Loh, Y., et al.. (2024). Prevalence of Hypertrophic Cardiomyopathy and ALMS1 Variant in Sphynx Cats in New Zealand. Animals. 14(18). 2629–2629. 1 indexed citations

Matos, José Novo, et al.. (2024). Longitudinal assessment of systolic anterior motion of the mitral valve in cats with hypertrophic cardiomyopathy. Journal of Veterinary Internal Medicine. 38(6). 2982–2993. 1 indexed citations

Dudhia, Jayesh, et al.. (2024). CRISPR/Cas9 gene editing in induced pluripotent stem cells to investigate the feline hypertrophic cardiomyopathy causing MYBPC3/R820W mutation. PLoS ONE. 19(10). e0311761–e0311761. 1 indexed citations

Drummond, Linda, et al.. (2023). Experiences of shared decision making in acute hospitals: A mixed methods secondary analysis of the Irish National Inpatient Experience Survey. Patient Education and Counseling. 113. 107755–107755. 3 indexed citations

Lawson, Charlotte, et al.. (2023). Exploration of Mediators Associated with Myocardial Remodelling in Feline Hypertrophic Cardiomyopathy. Animals. 13(13). 2112–2112. 4 indexed citations

Ho, Kim L., Qutuba G. Karwi, David J. Connolly, et al.. (2022). Metabolic, structural and biochemical changes in diabetes and the development of heart failure. Diabetologia. 65(3). 411–423. 41 indexed citations

Matos, José Novo, et al.. (2020). Biomarker changes with systolic anterior motion of the mitral valve in cats with hypertrophic cardiomyopathy. Journal of Veterinary Internal Medicine. 34(5). 1718–1727. 11 indexed citations

10.

Dudhia, Jayesh, et al.. (2019). Inducing Pluripotency in the Domestic Cat ( Felis catus ). Stem Cells and Development. 28(19). 1299–1309. 23 indexed citations

11.

Matos, José Novo, et al.. (2018). Selected feline abstracts from the Companion Animal Genetic Health conference 2018 (CAGH 2018): Irish Veterinary Journal. Irish Veterinary Journal. 71(S1). 1 indexed citations

12.

Borgeat, Kieran, et al.. (2018). Time spent with cats is never wasted: Lessons learned from feline acromegalic cardiomyopathy, a naturally occurring animal model of the human disease. PLoS ONE. 13(3). e0194342–e0194342. 20 indexed citations

13.

Dudhia, Jayesh, et al.. (2018). Cardiosphere-derived cells suppress allogeneic lymphocytes by production of PGE2 acting via the EP4 receptor. Scientific Reports. 8(1). 13351–13351. 10 indexed citations

14.

Connolly, David J., et al.. (2018). Pericardial effusion associated with systemic inflammatory disease in seven dogs (January 2006 – January 2012). Journal of Veterinary Cardiology. 20(2). 123–128. 7 indexed citations

15.

Messer, Andrew E., et al.. (2017). Investigations into the Sarcomeric Protein and Ca2+-Regulation Abnormalities Underlying Hypertrophic Cardiomyopathy in Cats (Felix catus). Frontiers in Physiology. 8. 348–348. 20 indexed citations

16.

Borgeat, Kieran, Joshua A. Stern, Kathryn M. Meurs, Virginia Luis Fuentes, & David J. Connolly. (2015). The influence of clinical and genetic factors on left ventricular wall thickness in Ragdoll cats. Journal of Veterinary Cardiology. 17. S258–S267. 14 indexed citations

17.

Borgeat, Kieran, et al.. (2014). Association of the myosin binding protein C3 mutation (MYBPC3 R820W) with cardiac death in a survey of 236 Ragdoll cats. Journal of Veterinary Cardiology. 16(2). 73–80. 28 indexed citations

18.

Connolly, David J., et al.. (2011). The effect of protease inhibition on the temporal stability of NT-proBNP in feline plasma at room temperature. Journal of Veterinary Cardiology. 13(1). 13–19. 7 indexed citations

19.

Pandit, Abhay, et al.. (2011). Monitoring mRNA in living cells in a 3D in vitro model using TAT-peptide linked molecular beacons. Lab on a Chip. 11(22). 3908–3908. 11 indexed citations

20.

Patteson, Mark, et al.. (2010). Effects of sample handling on serum N-terminal proB-type natriuretic peptide concentration in normal dogs and dogs with heart disease. Journal of Veterinary Cardiology. 12(1). 41–48. 12 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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