Jonathan T. Lu
- Molecular Biology top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Surgery
- Cellular and Molecular Neuroscience top 10%
- Epidemiology
- Co-authors
- Kenneth R. ChienWeinian ShouRobert S. KassHideko KasaharaMichael SchneiderHanying ChenZuocheng YangLourdes Acosta
- Topics
- Cardiac electrophysiology and arrhythmias (10 papers)Congenital heart defects research (7 papers)Cardiomyopathy and Myosin Studies (7 papers)
- Partner nations
- United StatesJapanCanada
In The Last Decade
Jonathan T. Lu
25 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 99
- Molecular Biology 1.3k
- Cardiology and Cardiovascular Medicine 695
- Surgery 235
- Cellular and Molecular Neuroscience 224
- Epidemiology 223
Countries citing papers authored by Jonathan T. Lu
This map shows the geographic impact of Jonathan T. Lu'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 Jonathan T. Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan T. Lu more than expected).
Fields of papers citing papers by Jonathan T. Lu
This network shows the impact of papers produced by Jonathan T. Lu. 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 Jonathan T. Lu. The network helps show where Jonathan T. Lu may publish in the future.
Co-authorship network of co-authors of Jonathan T. Lu
This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan T. Lu. A scholar is included among the top collaborators of Jonathan T. Lu 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 Jonathan T. Lu. Jonathan T. Lu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 8 | |
| 3 | 48 | |
| 4 | 26 | |
| 5 | 4 | |
| 6 | 148 | |
| 7 | 37 | |
| 8 | 61 | |
| 9 | 41 | |
| 10 | 35 | |
| 11 | 46 | |
| 12 | 120 | |
| 13 | 73 | |
| 14 | 53 | |
| 15 | 27 | |
| 16 | 328 | |
| 17 | 392 | |
| 18 | Gene-engineered models for genetic manipulation and functional analysis of the cardiovascular system in mice. | 3 |
| 19 | 14 | |
| 20 | 102 |
About Jonathan T. Lu
Jonathan T. Lu is a scholar working on Cardiology and Cardiovascular Medicine, Behavioral Neuroscience and Cellular and Molecular Neuroscience, having authored 25 papers that have together received 1.7k indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (10 papers), Congenital heart defects research (7 papers) and Cardiomyopathy and Myosin Studies (7 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (695 citations), Molecular Biology (1.3k citations) and Cellular and Molecular Neuroscience (224 citations). Jonathan T. Lu has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Kenneth R. Chien, Weinian Shou, Robert S. Kass, Hideko Kasahara, Michael Schneider, Hanying Chen, Zuocheng Yang, Lourdes Acosta, Simon J. Conway and Shideng Bao. Their work appears in journals such as Cell, The Journal of Cell Biology and Circulation Research.
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.