Kaavya Paruchuri
- Molecular Biology
- Immunology top 10%
- Hematology top 5%
- Cancer Research top 10%
- Genetics top 10%
- Co-authors
- Xudong LiaoMukesh K. JainKlaus H. KaestnerYuan LuChris A. FlaskKarine ClémentAnne HamikJulian Kim
- Topics
- Genetic Associations and Epidemiology (4 papers)Lipoproteins and Cardiovascular Health (4 papers)Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers)
- Cited by
- ImmunologyHematologyGenetics
- Partner nations
- United StatesSouth KoreaCanada
In The Last Decade
Kaavya Paruchuri
19 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Molecular Biology 476
- Immunology 380
- Hematology 189
- Cancer Research 177
- Genetics 159
Countries citing papers authored by Kaavya Paruchuri
This map shows the geographic impact of Kaavya Paruchuri'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 Kaavya Paruchuri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaavya Paruchuri more than expected).
Fields of papers citing papers by Kaavya Paruchuri
This network shows the impact of papers produced by Kaavya Paruchuri. 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 Kaavya Paruchuri. The network helps show where Kaavya Paruchuri may publish in the future.
Co-authorship network of co-authors of Kaavya Paruchuri
This figure shows the co-authorship network connecting the top 25 collaborators of Kaavya Paruchuri. A scholar is included among the top collaborators of Kaavya Paruchuri 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 Kaavya Paruchuri. Kaavya Paruchuri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 15 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | Clonal Hematopoiesis of Indeterminate Potential Predicts Adverse Outcomes in Patients With Atherosclerotic Cardiovascular Diseasebreakdown → | 83 |
| 10 | 4 | |
| 11 | 59 | |
| 12 | 25 | |
| 13 | Distinction of lymphoid and myeloid clonal hematopoiesisbreakdown → | 161 |
| 14 | 19 | |
| 15 | 5 | |
| 16 | 1 | |
| 17 | 5 | |
| 18 | 69 | |
| 19 | Krüppel-like factor 4 regulates macrophage polarizationbreakdown → | 601 |
| 20 | 88 |
About Kaavya Paruchuri
Kaavya Paruchuri is a scholar working on Hematology, Cardiology and Cardiovascular Medicine and Health Information Management, having authored 20 papers that have together received 1.2k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (4 papers), Lipoproteins and Cardiovascular Health (4 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers). The work is most often cited by research in Immunology (380 citations), Hematology (189 citations) and Genetics (159 citations). Kaavya Paruchuri has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Xudong Liao, Mukesh K. Jain, Klaus H. Kaestner, Yuan Lu, Chris A. Flask, Karine Clément, Anne Hamik, Julian Kim, Kurt Q. Lu and Ganapati H. Mahabeleshwar. Their work appears in journals such as Circulation, Journal of Clinical Investigation and Nature Medicine.
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.