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Personal genomes, quantitative dynamic omics and personalized medicine
George I Mias1, Michael Snyder1
1Department of Genetics, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA.
Personalized genomes and advanced omics technologies enable precise disease association and prevention. Longitudinal multi-omics profiling combined with computational modeling drives the future of personalized medicine.
Area of Science:
- Genomics and Bioinformatics
- Personalized Medicine
- Systems Biology
Background:
- Human Genome Project advancements enable personalized genome availability.
- Shift towards personalized disease associations using multi-omics data.
Purpose of the Study:
- To explore the integration of personal genomes with emerging omics technologies.
- To highlight the potential of these integrated approaches for personalized medicine.
- To emphasize disease prevention through quantitative biological modeling.
Main Methods:
- Leveraging personalized genome data.
- Utilizing transcriptomics, proteomics, metabolomics, and antibodyomics.
- Employing longitudinal omics profiling.
- Developing computational methodologies for data analysis and modeling.
Main Results:
- Availability of personal genomes and developing omics technologies.
- Potential for quantitative profiling of thousands of molecular components.
- Capability to probe temporal patterns in molecular and physiological states.
Conclusions:
- Integrated omics approaches offer precise personalized medicine.
- Focus extends beyond characterization and treatment to disease prevention.
- Novel computational models are essential for handling complex multi-omics data.
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