Bioinformatic challenges for pharmacogenomic study: tools for genomic data analysis DOI Creative Commons
Mariamena Arbitrio, Marianna Milano, Maria Lucibello

et al.

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 11, 2025

The sequencing of the human genome in 2003 marked a transformative shift from one-size-fits-all approach to personalized medicine, emphasizing patient-specific molecular and physiological characteristics. Advances technologies, Sanger methods Next-Generation Sequencing (NGS), have generated vast genomic datasets, enabling development tailored therapeutic strategies. Pharmacogenomics (PGx) has played pivotal role elucidating how genetic make-up influences inter-individual variability drug efficacy toxicity discovering predictive prognostic biomarkers. However, challenges persist interpreting polymorphic variants translating findings into clinical practice. Multi-omics data integration bioinformatics tools are essential for addressing these complexities, uncovering novel insights, advancing precision medicine. In this review, starting our experience PGx studies performed by DMET microarray platform, we propose guideline combining machine learning, statistical, network-based approaches simplify better understand complex analysis which can be adapted broader applications, fostering accessibility high-performance bioinformatics, also non-specialists. Moreover, describe an example bioinformatic used comprehensive integrative could allow translation insights

Language: Английский

Bioinformatic challenges for pharmacogenomic study: tools for genomic data analysis DOI Creative Commons
Mariamena Arbitrio, Marianna Milano, Maria Lucibello

et al.

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 11, 2025

The sequencing of the human genome in 2003 marked a transformative shift from one-size-fits-all approach to personalized medicine, emphasizing patient-specific molecular and physiological characteristics. Advances technologies, Sanger methods Next-Generation Sequencing (NGS), have generated vast genomic datasets, enabling development tailored therapeutic strategies. Pharmacogenomics (PGx) has played pivotal role elucidating how genetic make-up influences inter-individual variability drug efficacy toxicity discovering predictive prognostic biomarkers. However, challenges persist interpreting polymorphic variants translating findings into clinical practice. Multi-omics data integration bioinformatics tools are essential for addressing these complexities, uncovering novel insights, advancing precision medicine. In this review, starting our experience PGx studies performed by DMET microarray platform, we propose guideline combining machine learning, statistical, network-based approaches simplify better understand complex analysis which can be adapted broader applications, fostering accessibility high-performance bioinformatics, also non-specialists. Moreover, describe an example bioinformatic used comprehensive integrative could allow translation insights

Language: Английский

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