AIMC Topic: Pharmacogenetics

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Revisiting Warfarin Dosing Using Machine Learning Techniques.

Computational and mathematical methods in medicine
Determining the appropriate dosage of warfarin is an important yet challenging task. Several prediction models have been proposed to estimate a therapeutic dose for patients. The models are either clinical models which contain clinical and demographi...

Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies.

BMC medical informatics and decision making
BACKGROUND: Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics ...

Biomedical question answering using semantic relations.

BMC bioinformatics
BACKGROUND: The proliferation of the scientific literature in the field of biomedicine makes it difficult to keep abreast of current knowledge, even for domain experts. While general Web search engines and specialized information retrieval (IR) syste...

Integration of a prognostic gene module with a drug sensitivity module to identify drugs that could be repurposed for breast cancer therapy.

Computers in biology and medicine
BACKGROUND: Efficiently discovering low risk drugs is important for drug development. However, the heterogeneity in patient population complicates the prediction of the therapeutic efficiency. Drug repositioning aiming to discover new indications of ...

Enabling the curation of your pharmacogenetic study.

Clinical pharmacology and therapeutics
As pharmacogenomics becomes integrated into clinical practice, curation of published studies becomes increasingly important. At the Pharmacogenomics Knowledgebase (PharmGKB; www.pharmgkb.org), pharmacogenetic associations reported in published articl...

Prediction of drug gene associations via ontological profile similarity with application to drug repositioning.

Methods (San Diego, Calif.)
The amount of biomedical literature has been increasing rapidly during the last decade. Text mining techniques can harness this large-scale data, shed light onto complex drug mechanisms, and extract relation information that can support computational...

Expanding biobank pharmacogenomics through machine learning calls of structural variation.

Genetics
Biobanks linking genetic data with clinical health records provide exciting opportunities for pharmacogenomic (PGx) research on genetic variation and drug response. Designed as central and multiuse resources, biobanks can facilitate diverse PGx resea...

Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder.

Clinical and translational science
Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to identify the optimal genetic markers for predicting outcomes to antidepressant therapies. The primary...

Large-scale information retrieval and correction of noisy pharmacogenomic datasets through residual thresholded deep matrix factorization.

Briefings in bioinformatics
Pharmacogenomics studies are attracting an increasing amount of interest from researchers in precision medicine. The advances in high-throughput experiments and multiplexed approaches allow the large-scale quantification of drug sensitivities in mole...

Optimizing Treatment: The Role of Pharmacology, Genomics, and AI in Improving Patient Outcomes.

Drug development research
Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through personalized medicine, pharmacogenomics, and artificial intelligence (AI). The objective of the present study is to review the role of personalized me...