Phillipp Torkler

1.5k total citations · 1 hit paper
18 papers, 1.1k citations indexed

About

Phillipp Torkler is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Rheumatology. According to data from OpenAlex, Phillipp Torkler has authored 18 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 9 papers in Pulmonary and Respiratory Medicine and 3 papers in Rheumatology. Recurrent topics in Phillipp Torkler's work include Prostate Cancer Diagnosis and Treatment (9 papers), Prostate Cancer Treatment and Research (5 papers) and RNA and protein synthesis mechanisms (5 papers). Phillipp Torkler is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (9 papers), Prostate Cancer Treatment and Research (5 papers) and RNA and protein synthesis mechanisms (5 papers). Phillipp Torkler collaborates with scholars based in Germany, United States and Sweden. Phillipp Torkler's co-authors include Carlo Baejen, Patrick Cramer, Johan Skog, Mikkel Noerholm, Michael Donovan, James M. McKiernan, Gero Doose, Dmitrij Frishman, Pawel Smialowski and Stefanie Kaufmann and has published in prestigious journals such as Cell, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Phillipp Torkler

18 papers receiving 1.1k citations

Hit Papers

A Prospective Adaptive Utility Trial to Validate Performa... 2018 2026 2020 2023 2018 50 100 150 200
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.

  1. A Prospective Adaptive Utility Trial to Validate Performance of a Novel Urine Exosome Gene Expression Assay to Predict High-grade Prostate Cancer in Patients with Prostate-specific Antigen 2–10 ng/ml at Initial Biopsy
    2018 209 citations James M. McKiernan, Michael Donovan et al. European Urology profile →

Peers

Phillipp Torkler
Mingchao Wang China
Markus Sprenger‐Haussels Germany
Hirokazu Kimura Japan
Ann S. G. Lee Singapore
Rüdiger Rüger Germany
Christina Beinke Germany
Ding Ma China
Θεόδωρος Ράμπιας Greece
Eugene Dempsey Ireland
Mingchao Wang China
Phillipp Torkler
Citations per year, relative to Phillipp Torkler Phillipp Torkler (= 1×) peers Mingchao Wang

Countries citing papers authored by Phillipp Torkler

Since Specialization
Citations

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

Fields of papers citing papers by Phillipp Torkler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Phillipp Torkler

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

All Works

18 of 18 papers shown
1.
Torkler, Phillipp, et al.. (2024). LoDEI: a robust and sensitive tool to detect transcriptome-wide differential A-to-I editing in RNA-seq data. Nature Communications. 15(1). 9121–9121. 5 indexed citations
2.
Kretschmer, Alexander, Ronald Tutrone, Jason Alter, et al.. (2022). Pre-diagnosis urine exosomal RNA (ExoDx EPI score) is associated with post-prostatectomy pathology outcome. World Journal of Urology. 40(4). 983–989. 29 indexed citations
3.
Kretschmer, Alexander, Eric Margolis, Ronald Tutrone, et al.. (2022). Validation of a CE-IVD, urine exosomal RNA expression assay for risk assessment of prostate cancer prior to biopsy. Scientific Reports. 12(1). 4777–4777. 31 indexed citations
4.
Torkler, Phillipp, et al.. (2022). Importance and implications of exosomes in nephrology and urology. Pflügers Archiv - European Journal of Physiology. 475(2). 153–166. 5 indexed citations
5.
Brown, Gordon, Alan W. Partin, Ballentine Carter, et al.. (2021). Predicting high-grade prostate cancer at initial biopsy: clinical performance of the ExoDx (EPI) Prostate Intelliscore test in three independent prospective studies. Prostate Cancer and Prostatic Diseases. 25(2). 296–301. 66 indexed citations
6.
McKiernan, James M., Mikkel Noerholm, Vasisht Tadigotla, et al.. (2020). A urine-based Exosomal gene expression test stratifies risk of high-grade prostate Cancer in men with prior negative prostate biopsy undergoing repeat biopsy. BMC Urology. 20(1). 138–138. 35 indexed citations
7.
Tutrone, Ronald, Michael Donovan, Phillipp Torkler, et al.. (2020). Clinical utility of the exosome based ExoDx Prostate(IntelliScore) EPI test in men presenting for initial Biopsy with a PSA 2–10 ng/mL. Prostate Cancer and Prostatic Diseases. 23(4). 607–614. 123 indexed citations
8.
McKiernan, James M., Ronald Tutrone, Michael Donovan, et al.. (2020). Urine exosome gene expression assay net benefit analysis in a large pooled cohort.. Journal of Clinical Oncology. 38(6_suppl). 287–287. 1 indexed citations
9.
McKiernan, James M., Michael Donovan, Eric Margolis, et al.. (2018). A Prospective Adaptive Utility Trial to Validate Performance of a Novel Urine Exosome Gene Expression Assay to Predict High-grade Prostate Cancer in Patients with Prostate-specific Antigen 2–10 ng/ml at Initial Biopsy. European Urology. 74(6). 731–738. 209 indexed citations breakdown →
10.
Donovan, Michael, Phillipp Torkler, Mikkel Noerholm, Johan Skog, & James M. McKiernan. (2018). Performance of a clinically validated urine exosome gene expression test to predict high grade prostate cancer in men with a prior negative biopsy.. Journal of Clinical Oncology. 36(6_suppl). 119–119. 2 indexed citations
11.
Baejen, Carlo, Jessica Andréani, Phillipp Torkler, et al.. (2017). Genome-wide Analysis of RNA Polymerase II Termination at Protein-Coding Genes. Molecular Cell. 66(1). 38–49.e6. 86 indexed citations
12.
Donovan, Michael, Phillipp Torkler, Mikkel Noerholm, Johan Skog, & James M. McKiernan. (2017). MP33-05 RADICAL PROSTATECTOMY OUTCOMES FROM A VALIDATED URINE EXOSOME GENE EXPRESSION ASSAY WHICH PREDICTS HIGH-GRADE (GS7) PROSTATE CANCER SUGGESTS UTILITY FOR MEN ENROLLED IN ACTIVE SURVEILLANCE.. The Journal of Urology. 197(4S). 1 indexed citations
13.
Battaglia, Sofia, Michael Lidschreiber, Carlo Baejen, et al.. (2017). RNA-dependent chromatin association of transcription elongation factors and Pol II CTD kinases. eLife. 6. 44 indexed citations
14.
15.
Baejen, Carlo, Phillipp Torkler, Saskia Gressel, et al.. (2014). Transcriptome Maps of mRNP Biogenesis Factors Define Pre-mRNA Recognition. Molecular Cell. 55(5). 745–757. 89 indexed citations
16.
Schulz, Daniel, Björn Schwalb, Anja Kiesel, et al.. (2013). Transcriptome Surveillance by Selective Termination of Noncoding RNA Synthesis. Cell. 155(5). 1075–1087. 164 indexed citations
17.
Smialowski, Pawel, Gero Doose, Phillipp Torkler, Stefanie Kaufmann, & Dmitrij Frishman. (2012). PROSO II – a new method for protein solubility prediction. FEBS Journal. 279(12). 2192–2200. 168 indexed citations
18.
Zacher, Benedikt, Phillipp Torkler, & Achim Tresch. (2011). Analysis of Affymetrix ChIP-Chip Data Using Starr and R/Bioconductor. Cold Spring Harbor Protocols. 2011(5). pdb.top110–pdb.top110. 6 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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