Attila Kovács

5.9k citations
62 papers · 4.8k indexed · 3 hit papers · h-index 28

Attila Kovács

60 papers receiving 4.7k citations

Hit Papers

The cardiac phenotype induced by PPARα overexpression mim...66320002026200820172505007501000

Peers

Attila Kovács
Comparison fields: 5 of 110
  • Physiology 2.2k
  • Cardiology and Cardiovascular Medicine 1.5k
  • Molecular Biology 3.0k
  • Cell Biology 619
  • Biochemistry 265
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Rick B. Vega United States
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Kerstin Boengler Germany
Sandrine Horman Belgium
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Attila Kovács relative to Rick B. Vega United States Rick B. Vega's profile →
Citations per field
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Citations per year

Countries citing papers authored by Attila Kovács

Since Specialization
Citations

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

Fields of papers citing papers by Attila Kovács

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Attila Kovács, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Attila Kovács Line = papers co-authored together Attila Kovács links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20254
3 20240
4 20241
5 20247
6 20232
7 20239
8 202118
9 201919
10 201818
11 201719
12 20165
13 201447
14 200923
15 2008261
16 200750
17 200629
18 200473
19
The cardiac phenotype induced by PPARα overexpression mimics that caused by diabetes mellitusbreakdown →
2002663
20
Peroxisome proliferator–activated receptor γ coactivator-1 promotes cardiac mitochondrial biogenesisbreakdown →
20001058

About Attila Kovács

Attila Kovács is a scholar working on Physiology, Physiology and Cell Biology, having authored 62 papers that have together received 4.8k indexed citations. Recurring topics across this work include Lysosomal Storage Disorders Research (26 papers), Cellular transport and secretion (14 papers), Cardiovascular Function and Risk Factors (10 papers), Neuroscience and Neuropharmacology Research (8 papers), Mitochondrial Function and Pathology (7 papers), Peroxisome Proliferator-Activated Receptors (6 papers), Calcium signaling and nucleotide metabolism (6 papers) and Cardiac Structural Anomalies and Repair (5 papers). The work is most often cited by research in Physiology (2.2k citations), Cardiology and Cardiovascular Medicine (1.5k citations) and Molecular Biology (3.0k citations). Attila Kovács has collaborated with scholars based in United States, Hungary and United Kingdom. Frequent co-authors include Jeffrey E. Saffitz, Daniel P. Kelly, John J. Lehman, Denis M. Medeiros, David A. Pearce, Philip M. Barger, Teresa C. Leone, Ricardo Garcı́a, Fong‐Fu Hsu and Jean E. Schaffer. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

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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