Document - AI applications in functional genomics

2021

Journal article Open Access

AI applications in functional genomics

Caudai C., Galizia A., Geraci F., Le Pera L., Morea V., Salerno E., Via A., Colombo T.

Artificial intelligence Functional genomics Genomics Proteomics Epigenomics Transcriptomics Epitranscriptomics Metabolomics Machine learning Deep learning

We review the current applications of artificial intelligence (AI) in functional genomics. The recent explosion of AI follows the remarkable achievements made possible by ''deep learning", along with a burst of ''big data" that can meet its hunger. Biology is about to overthrow astronomy as the paradigmatic representative of big data producer. This has been made possible by huge advancements in the field of high throughput technologies, applied to determine how the individual components of a biological system work together to accomplish different processes. The disciplines contributing to this bulk of data are collectively known as functional genomics. They consist in studies of: i) the information contained in the DNA (genomics); ii) the modifications that DNA can reversibly undergo (epigenomics); iii) the RNA transcripts originated by a genome (transcriptomics); iv) the ensemble of chemical modifications decorating different types of RNA transcripts (epitranscriptomics); v) the products of protein-coding transcripts (proteomics); and vi) the small molecules produced from cell metabolism (metabolomics) present in an organism or system at a given time, in physiological or pathological conditions. After reviewing main applications of AI in functional genomics, we discuss important accompanying issues, including ethical, legal and economic issues and the importance of explainability.

Source: Computational and Structural Biotechnology Journal 19 (2021): 5762–5790. doi:10.1016/j.csbj.2021.10.009

Publisher: Chalmers University of Technology,, Göteborg , Svezia

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@article{oai:it.cnr:prodotti:458104,
	title = {AI applications in functional genomics},
	author = {Caudai C. and Galizia A. and Geraci F. and Le Pera L. and Morea V. and Salerno E. and Via A. and Colombo T.},
	publisher = {Chalmers University of Technology,, Göteborg , Svezia},
	doi = {10.1016/j.csbj.2021.10.009},
	journal = {Computational and Structural Biotechnology Journal},
	volume = {19},
	pages = {5762–5790},
	year = {2021}
}