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Towards multi-omics synthetic data integration
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DOI：10.1093/bib/bbae213.png)
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Abstract
En 中文
Across many scientific disciplines, the development of computational models and algorithms for generating artificial or synthetic data is gaining momentum. In biology, there is a great opportunity to explore this further as more and more big data at multi-omics level are generated recently. In this opinion, we discuss the latest trends in biological applications based on process-driven and data-driven aspects. Moving ahead, we believe these methodologies can help shape novel multi-omics-scale cellular inferences.
Keywords:
synthetic data
process-driven
data-driven
machine learning
multi-omics
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