Philipp Rentzsch
Molecular Biology · 2018–2021
A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 94 citations into it
- Genetics — 61 citations into it
- Computational Biology & Bioinformatics — 13 citations into it
Whom Philipp Rentzsch trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- James Y. Zou
- Heng Li
- Pauline Crystal Ng
- Jason Ernst
- Vojtech Franc
- Fernando Racimo
- Gregory M. Cooper
- Xiaoming Liu
- Jian Zhou
- Ivan A. Adzhubei
Who trusts Philipp Rentzsch overall
Papers from Philipp Rentzsch's perspective
Ordered by how strongly the researchers Philipp Rentzsch trusts endorse each paper. Same corpus, a different order for every researcher.
- A method and server for predicting damaging missense mutations
- Unsupervised pattern discovery in human chromatin structure through genomic segmentation
- Potential etiologic and functional implications of genome-wide association loci for human diseases and traits (Proceedings of the National Academy of Sciences of the United States of America)
- Predicting the functional impact of protein mutations: application to cancer genomics
- A general framework for estimating the relative pathogenicity of human genetic variants
- Enredo and Pecan: genome-wide mammalian consistency-based multiple alignment with paralogs. (Genome Research)
- Predicting the Functional Effect of Amino Acid Substitutions and Indels
- Bioinformatics Applications Note Databases and Ontologies Deriving the Consequences of Genomic Variants with the Ensembl Api and Snp Effect Predictor
- ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
- Identifying novel constrained elements by exploiting biased substitution patterns
Their papers
- CADD: predicting the deleteriousness of variants throughout the human genome (2018) — 3,218 citations
- CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores (2021) — 563 citations