Paul Perco

4.2k total citations · 1 hit paper
108 papers, 3.0k citations indexed

About

Paul Perco is a scholar working on Molecular Biology, Nephrology and Surgery. According to data from OpenAlex, Paul Perco has authored 108 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Molecular Biology, 26 papers in Nephrology and 20 papers in Surgery. Recurrent topics in Paul Perco's work include Chronic Kidney Disease and Diabetes (20 papers), Bioinformatics and Genomic Networks (20 papers) and Renal Transplantation Outcomes and Treatments (18 papers). Paul Perco is often cited by papers focused on Chronic Kidney Disease and Diabetes (20 papers), Bioinformatics and Genomic Networks (20 papers) and Renal Transplantation Outcomes and Treatments (18 papers). Paul Perco collaborates with scholars based in Austria, United States and Germany. Paul Perco's co-authors include Bernd Mayer, Rainer Oberbauer, Gert Mayer, Andreas Heinzel, Gert Mayer, Alexander Kainz, Arno Lukas, Hiddo J.L. Heerspink, Johannes Leierer and Bernd Mayer and has published in prestigious journals such as Annals of Internal Medicine, PLoS ONE and Biomaterials.

In The Last Decade

Paul Perco

106 papers receiving 2.9k citations

Hit Papers

Canagliflozin reduces inflammation and fibrosis biomarker... 2019 2026 2021 2023 2019 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
Paul Perco Austria 30 1.1k 579 573 356 349 108 3.0k
Holger Schmid Germany 28 1.1k 1.0× 308 0.5× 1.3k 2.2× 134 0.4× 111 0.3× 66 3.3k
John P. Dowling Australia 38 1.2k 1.1× 353 0.6× 1.2k 2.1× 348 1.0× 122 0.3× 128 4.5k
Marie Essig France 31 489 0.4× 726 1.3× 572 1.0× 95 0.3× 718 2.1× 114 2.8k
Michael P. Madaio United States 46 1.4k 1.3× 270 0.5× 1.4k 2.5× 112 0.3× 77 0.2× 138 7.7k
Reinhart Willers Germany 30 542 0.5× 738 1.3× 227 0.4× 83 0.2× 129 0.4× 85 2.8k
Ian Chin‐Yee Canada 27 615 0.6× 344 0.6× 141 0.2× 134 0.4× 76 0.2× 127 4.0k
Norio Yoshimura Japan 29 512 0.5× 1.1k 1.9× 327 0.6× 71 0.2× 987 2.8× 241 3.2k
Griffin P. Rodgers United States 42 1.5k 1.4× 379 0.7× 152 0.3× 158 0.4× 45 0.1× 174 6.7k
Adam Lane United States 31 412 0.4× 229 0.4× 406 0.7× 42 0.1× 542 1.6× 194 3.5k
David Barnett United Kingdom 38 1.4k 1.3× 181 0.3× 93 0.2× 123 0.3× 74 0.2× 134 4.3k

Countries citing papers authored by Paul Perco

Since Specialization
Citations

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

Fields of papers citing papers by Paul Perco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Perco

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Perco. A scholar is included among the top collaborators of Paul Perco 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 Paul Perco. Paul Perco 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.
Fillinger, Lucas, et al.. (2025). Computational modeling approaches and regulatory pathways for drug combinations. Drug Discovery Today. 30(5). 104345–104345. 3 indexed citations
2.
Perco, Paul, et al.. (2025). Computational Drug Repositioning in Cardiorenal Disease: Opportunities, Challenges, and Approaches. PROTEOMICS. 25(11-12). e202400109–e202400109. 1 indexed citations
5.
Ley, Matthias, Lucas Fillinger, Paul Perco, et al.. (2024). Investigation of the Urinary Peptidome to Unravel Collagen Degradation in Health and Kidney Disease. PROTEOMICS. 25(11-12). e202400279–e202400279. 3 indexed citations
6.
Gebeshuber, Christoph A., Heinz Regele, Helga Schachner, et al.. (2023). Computational drug repositioning of clopidogrel as a novel therapeutic option for focal segmental glomerulosclerosis. Translational research. 259. 28–34. 6 indexed citations
7.
Beige, Joachim, Justyna Siwy, Alexandre Mebazaa, et al.. (2023). Urinary peptides provide information about the risk of mortality across a spectrum of diseases and scenarios. Journal of Translational Medicine. 21(1). 663–663. 2 indexed citations
8.
Nair, Viji, Johannes Leierer, Michael Rudnicki, et al.. (2022). Assessment of Fibrinogen-like 2 (FGL2) in Human Chronic Kidney Disease through Transcriptomics Data Analysis. Biomolecules. 13(1). 89–89. 4 indexed citations
9.
Effenberger, Maria, Andreas Kronbichler, Felix Grabherr, et al.. (2021). Using Infodemiology Metrics to Assess Public Interest in Liver Transplantation: Google Trends Analysis. Journal of Medical Internet Research. 23(8). e21656–e21656. 3 indexed citations
10.
Kratochwill, Klaus, et al.. (2021). A Meta-Analysis of Human Transcriptomics Data in the Context of Peritoneal Dialysis Identifies Novel Receptor-Ligand Interactions as Potential Therapeutic Targets. International Journal of Molecular Sciences. 22(24). 13277–13277. 2 indexed citations
11.
Effenberger, Maria, Andreas Kronbichler, Jae Il Shin, et al.. (2020). Association of the COVID-19 pandemic with Internet Search Volumes: A Google TrendsTM Analysis. International Journal of Infectious Diseases. 95. 192–197. 177 indexed citations
12.
Sauer, Ursula, Andreas Heinzel, Paul Perco, et al.. (2016). Validation of a protein panel for the noninvasive detection of recurrent non-muscle invasive bladder cancer. Biomarkers. 22(7). 674–681. 19 indexed citations
13.
Bernthaler, Andreas, et al.. (2011). Linking molecular feature space and disease terms for the immunosuppressive drugrapamycin. Molecular BioSystems. 7(10). 2863–2871. 1 indexed citations
14.
El‐Gazzar, Ahmed, Paul Perco, Eva Eckelhart, et al.. (2010). Natural Immunity Enhances the Activity of a DR5 Agonistic Antibody and Carboplatin in the Treatment of Ovarian Cancer. Molecular Cancer Therapeutics. 9(4). 1007–1018. 16 indexed citations
15.
Barth, Susanne, Tsviya Olender, Andreea Munteanu, et al.. (2010). Synthetic lethal hubs associated with vincristine resistant neuroblastoma. Molecular BioSystems. 7(1). 200–214. 8 indexed citations
16.
Kainz, Alexander, Julia Wilflingseder, Christa Mitterbauer, et al.. (2010). Steroid Pretreatment of Organ Donors to Prevent Postischemic Renal Allograft Failure. Annals of Internal Medicine. 4 indexed citations
17.
Schramek, Herbert, Andreas Kronbichler, Markus Pirklbauer, et al.. (2009). Neuropilin-1 and neuropilin-2 are differentially expressed in human proteinuric nephropathies and cytokine-stimulated proximal tubular cells. Laboratory Investigation. 89(11). 1304–1316. 28 indexed citations
18.
Bernthaler, Andreas, et al.. (2009). A dependency graph approach for the analysis of differential gene expression profiles. Molecular BioSystems. 5(12). 1720–1731. 25 indexed citations
19.
Rudnicki, Michael A., Paul Perco, Susanne Eder, et al.. (2009). Hypoxia response and VEGF-A expression in human proximal tubular epithelial cells in stable and progressive renal disease. Laboratory Investigation. 89(3). 337–346. 91 indexed citations
20.
Wilflingseder, Julia, et al.. (2008). Molecular predictors for anaemia after kidney transplantation. Nephrology Dialysis Transplantation. 24(3). 1015–1023. 5 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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