Philipp Rentzsch

4.5k total citations · 2 hit papers
6 papers, 2.2k citations indexed

About

Philipp Rentzsch is a scholar working on Molecular Biology, Genetics and Infectious Diseases. According to data from OpenAlex, Philipp Rentzsch has authored 6 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Genetics and 0 papers in Infectious Diseases. Recurrent topics in Philipp Rentzsch's work include Genomics and Rare Diseases (2 papers), RNA modifications and cancer (2 papers) and Bioinformatics and Genomic Networks (2 papers). Philipp Rentzsch is often cited by papers focused on Genomics and Rare Diseases (2 papers), RNA modifications and cancer (2 papers) and Bioinformatics and Genomic Networks (2 papers). Philipp Rentzsch collaborates with scholars based in Germany, United States and Sweden. Philipp Rentzsch's co-authors include Jay Shendure, Martin Kircher, Daniela Witten, Gregory M. Cooper, Max Schubach, Jeongbin Park, Carolin Andresen, Matthias Schlesner, Carl Herrmann and Andrés Quintero and has published in prestigious journals such as Nucleic Acids Research, Genome Research and Genome Medicine.

In The Last Decade

Philipp Rentzsch

5 papers receiving 2.2k citations

Hit Papers

align trajectories

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.

CADD: predicting the deleteriousness of variants throughout the human genome

2018 1.9k citations Philipp Rentzsch, Daniela Witten et al. Nucleic Acids Research profile →
CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores

2021 320 citations Philipp Rentzsch, Max Schubach et al. Genome Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Philipp Rentzsch Germany	3	1.3k	1.1k	234	135	134	6	2.2k
Eissa Faqeih Saudi Arabia	28	1.5k 1.1×	920 0.8×	159 0.7×	98 0.7×	143 1.1×	80	2.2k
Masoud Garshasbi Iran	24	1.5k 1.1×	729 0.7×	354 1.5×	66 0.5×	254 1.9×	127	2.4k
Shaun S. Abeysinghe United Kingdom	8	1.4k 1.1×	845 0.8×	186 0.8×	86 0.6×	80 0.6×	8	2.1k
Steven M. Harrison United States	22	1.5k 1.1×	1.7k 1.5×	443 1.9×	125 0.9×	84 0.6×	52	3.2k
Alfredo Brusco Italy	32	2.2k 1.7×	799 0.7×	170 0.7×	158 1.2×	223 1.7×	141	3.3k
Philip D. Cotter United States	26	1.3k 1.0×	994 0.9×	298 1.3×	247 1.8×	153 1.1×	95	2.4k
Diana Baralle United Kingdom	24	1.8k 1.4×	761 0.7×	173 0.7×	153 1.1×	110 0.8×	84	2.7k
Süleyman Gülsüner United States	21	795 0.6×	736 0.7×	223 1.0×	73 0.5×	129 1.0×	43	1.7k
Claudia Ruivenkamp Netherlands	31	1.8k 1.4×	1.8k 1.6×	292 1.2×	133 1.0×	341 2.5×	79	3.4k
Jessica X. Chong United States	19	769 0.6×	687 0.6×	145 0.6×	92 0.7×	85 0.6×	44	1.4k

Countries citing papers authored by Philipp Rentzsch

Since Specialization

Citations

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

Fields of papers citing papers by Philipp Rentzsch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philipp Rentzsch

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

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Rentzsch, Philipp, et al.. (2025). varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction. Genome Medicine. 17(1). 84–84. 1 indexed citations

2.

Rentzsch, Philipp, et al.. (2025). Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes. Genome Research. 35(10). 2316–2325.

3.

Domingo, Júlia, et al.. (2024). Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs. NAR Genomics and Bioinformatics. 7(1). lqae178–lqae178. 1 indexed citations

4.

Rentzsch, Philipp, Max Schubach, Jay Shendure, & Martin Kircher. (2021). CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores. Genome Medicine. 13(1). 320 indexed citations breakdown →

5.

Quintero, Andrés, Daniel Hübschmann, Nils Kurzawa, et al.. (2020). ShinyButchR: Interactive NMF-based decomposition workflow of genome-scale datasets. Biology Methods and Protocols. 5(1). bpaa022–bpaa022. 9 indexed citations

6.

Rentzsch, Philipp, Daniela Witten, Gregory M. Cooper, Jay Shendure, & Martin Kircher. (2018). CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Research. 47(D1). D886–D894. 1914 indexed citations breakdown →

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.

Explore authors with similar magnitude of impact