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On fusion methods for knowledge discovery from multi-omics datasets - PubMed
Source: pubmed.ncbi.nlm.nih.gov
Article summary:
1. Multi-omics measurements are becoming increasingly popular for understanding how biological activities on varying levels are perturbed by genetic variants, environments, and their interactions.
2. Fusion-based analysis has advanced rapidly in the past decade due to application drivers and theoretical breakthroughs in mathematics, statistics, and computer science.
3. There are three types of fusion methods: data fusion, model fusion, and mixed fusion.
Article analysis:
The article is generally reliable and trustworthy as it provides a comprehensive overview of the current state of knowledge regarding fusion methods for knowledge discovery from multi-omics datasets. The authors provide a clear explanation of the different types of fusion methods (data fusion, model fusion, and mixed fusion) as well as examples to illustrate each type. Furthermore, the authors discuss potential issues that need to be addressed in future studies.
However, there are some potential biases that should be noted. For example, the article does not provide any counterarguments or alternative perspectives on the topic which could lead to a one-sided reporting of the issue. Additionally, there is no discussion of possible risks associated with using these methods which could lead to an incomplete understanding of their implications. Finally, there is no mention of any promotional content which could lead readers to believe that all aspects of these methods have been explored when this may not be the case.