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Pharmacogenetics

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Precision psychiatry in clinical practice.

International journal of psychiatry in clinical practice
The treatment of depression represents a major challenge for healthcare systems and choosing among the many available drugs without objective guidance criteria is an error-prone process. Recently, pharmacogenetic biomarkers entered in prescribing gui...

PharmGKB Tutorial for Pharmacogenomics of Drugs Potentially Used in the Context of COVID-19.

Clinical pharmacology and therapeutics
Pharmacogenomics (PGx) is a key area of precision medicine, which is already being implemented in some health systems and may help guide clinicians toward effective therapies for individual patients. Over the last 2 decades, the Pharmacogenomics Know...

The Human Phenotype Ontology in 2021.

Nucleic acids research
The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for ...

Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Nature communications
Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and Drug Administration (FDA) for another indication i...

Opportunities and challenges for the computational interpretation of rare variation in clinically important genes.

American journal of human genetics
Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of variants in an individual's genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic vari...

Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics.

Molecular diversity
Convolutional neural networks (CNNs) have been used to extract information from various datasets of different dimensions. This approach has led to accurate interpretations in several subfields of biological research, like pharmacogenomics, addressing...

Performance Comparisons of AlexNet and GoogLeNet in Cell Growth Inhibition IC50 Prediction.

International journal of molecular sciences
Drug responses in cancer are diverse due to heterogenous genomic profiles. Drug responsiveness prediction is important in clinical response to specific cancer treatments. Recently, multi-class drug responsiveness models based on deep learning (DL) mo...

DeepDRK: a deep learning framework for drug repurposing through kernel-based multi-omics integration.

Briefings in bioinformatics
Recent pharmacogenomic studies that generate sequencing data coupled with pharmacological characteristics for patient-derived cancer cell lines led to large amounts of multi-omics data for precision cancer medicine. Among various obstacles hindering ...

Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning models.

Briefings in bioinformatics
The goal of precision oncology is to tailor treatment for patients individually using the genomic profile of their tumors. Pharmacogenomics datasets such as cancer cell lines are among the most valuable resources for drug sensitivity prediction, a cr...