Journal
BIOMARKER RESEARCH
Volume 5, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s40364-017-0082-y
Keywords
Genomics; Pharmacogenomics; Single nucleotide polymorphisms; Machine learning; Multi-omics; Systems genomics
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Funding
- Ministry of Economic Affairs in Taiwan (SBIR) [S099000280249-154]
- Taiwan Ministry of Health and Welfare Clinical Trial and Research Center of Excellence [MOHW105-TDU-B-212-133019]
- China Medical University Hospital, Taiwan [DMR-101-091, DMR-102-069]
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In light of recent advances in biomedical computing, big data science, and precision medicine, there is a mammoth demand for establishing algorithms in machine learning and systems genomics (MLSG), together with multi-omics data, to weigh probable phenotype-genotype relationships. Software frameworks in MLSG are extensively employed to analyze hundreds of thousands of multi-omics data by high-throughput technologies. In this study, we reviewed the MLSG software frameworks and future directions with respect to multi-omics data analysis and integration. Our review was targeted at researching recent approaches and technical solutions for the MLSG software frameworks using multi-omics platforms.
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