ReviewFrontiers in pharmacology2018
Computational Methods for the Pharmacogenetic Interpretation of Next Generation Sequencing Data.
Review in Frontiers in pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
36 citing papers in PubMed, 73 citations in OpenAlex.
- Feed-Forward Deep Neural Networks Predict Substrate-Specific Effects of Transporter Variants to Explain Drug Response Variability.Clinical and translational science · 2026Article
- The evolving landscape of pharmacogenomics: Current achievements and future directions.Pharmacological reviews · 2026Review
- Translating pharmacogenomic sequencing data into drug response predictions-How to interpret variants of unknown significance.British journal of clinical pharmacology · 2025Review
- Polygenic modelling and machine learning approaches in pharmacogenomics: Importance in downstream analysis of genome-wide association study data.British journal of clinical pharmacology · 2025Review
- Pharmacogenomics: A Genetic Approach to Drug Development and Therapy.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Clinical Implementation of Rare and NovelInternational journal of biological sciences · 2024Review
- Pharmacovariome scanning using whole pharmacogene resequencing coupled with deep computational analysis and machine learning for clinical pharmacogenomics.Human genomics · 2023Article
- Pharmacogenomic profile of actionable molecular variants related to drugs commonly used in anesthesia: WES analysis reveals new mutations.Frontiers in pharmacology · 2023Article
- Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy.Handbook of experimental pharmacology · 2023Article
- A paradigm shift in pharmacogenomics: From candidate polymorphisms to comprehensive sequencing.Basic & clinical pharmacology & toxicology · 2022Review
- Genome interpretation using in silico predictors of variant impact.Human genetics · 2022Review
- Characterization of NovelJournal of personalized medicine · 2022Article
- Clinical pharmacogenetic analysis in 5,001 individuals with diagnostic Exome Sequencing data.NPJ genomic medicine · 2022Article
- Pharmacogenomics of statins: lipid response and other outcomes in Brazilian cohorts.Pharmacological reports : PR · 2022Review
- Genetic landscape of 125 pharmacogenes in Chinese from the Chinese Millionome Database.Scientific reports · 2021Article
- Rare genetic variability in human drug target genes modulates drug response and can guide precision medicine.Science advances · 2021Article
- Pharmacogenomic Biomarkers of Follicle-Stimulating Hormone Receptor Malfunction in Females with Impaired Ovarian Response-A Genetic Survey.Journal of clinical medicine · 2021Review
- Efficacy of computational predictions of the functional effect of idiosyncratic pharmacogenetic variants.PeerJ · 2021Article
- Applying Next-Generation Sequencing Platforms for Pharmacogenomic Testing in Clinical Practice.Frontiers in pharmacology · 2021Review
- Variation in 100 relevant pharmacogenes among emiratis with insights from understudied populations.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Up to half of all patients do not respond to pharmacological treatment as intended. A substantial fraction of these inter-individual differences is due to heritable factors and a growing number of associations between genetic variations and drug response phenotypes have been identified. Importantly, the rapid progress in Next Generation Sequencing technologies in recent years unveiled the true complexity of the genetic landscape in pharmacogenes with tens of thousands of rare genetic variants. As each individual was found to harbor numerous such rare variants they are anticipated to be important contributors to the genetically encoded inter-individual variability in drug effects. The fundamental challenge however is their functional interpretation due to the sheer scale of the problem that renders systematic experimental characterization of these variants currently unfeasible. Here, we review concepts and important progress in the development of computational prediction methods that allow to evaluate the effect of amino acid sequence alterations in drug metabolizing enzymes and transporters. In addition, we discuss recent advances in the interpretation of functional effects of non-coding variants, such as variations in splice sites, regulatory regions and miRNA binding sites. We anticipate that these methodologies will provide a useful toolkit to facilitate the integration of the vast extent of rare genetic variability into drug response predictions in a precision medicine framework.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.