Supporting precision medicine by data mining across multi-disciplines: an integrative approach for generating comprehensive linkages between single nucleotide variants (SNVs) and drug-binding sites
| Autor: | Tiejun Cheng, Stephen H. Bryant, Amrita Roy Choudhury, Yanli Wang, Lon Phan |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Statistics and Probability Drug Metabolizing enzymes media_common.quotation_subject Context (language use) Biology computer.software_genre Polymorphism Single Nucleotide Biochemistry 03 medical and health sciences Gene Frequency Sequence Analysis Protein Protein methods Data Mining Humans Precision Medicine Molecular Biology Allele frequency media_common Binding Sites Sequence Analysis DNA Integrated approach Precision medicine Original Papers Computer Science Applications Minor allele frequency Computational Mathematics 030104 developmental biology Computational Theory and Mathematics Data mining computer Protein Binding |
| Zdroj: | Bioinformatics. 33:1621-1629 |
| ISSN: | 1367-4811 1367-4803 |
| DOI: | 10.1093/bioinformatics/btx031 |
| Popis: | Motivation Genetic variants in drug targets and metabolizing enzymes often have important functional implications, including altering the efficacy and toxicity of drugs. Identifying single nucleotide variants (SNVs) that contribute to differences in drug response and understanding their underlying mechanisms are fundamental to successful implementation of the precision medicine model. This work reports an effort to collect, classify and analyze SNVs that may affect the optimal response to currently approved drugs. Results An integrated approach was taken involving data mining across multiple information resources including databases containing drugs, drug targets, chemical structures, protein–ligand structure complexes, genetic and clinical variations as well as protein sequence alignment tools. We obtained 2640 SNVs of interest, most of which occur rarely in populations (minor allele frequency Availability and Implementation Data are available from Supplementary information file. Supplementary information Supplementary Tables S1–S5 are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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