AI applications in functional genomics
| Autor: | Allegra Via, Claudia Caudai, Loredana Le Pera, Veronica Morea, Filippo Geraci, Emanuele Salerno, Antonella Galizia, Teresa Colombo |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Proteomics
Epigenomics Artificial intelligence Computer science Big data Biophysics Genomics Review Computational biology Biochemistry Structural Biology Epitranscriptomics Machine learning Genetics Metabolomics Transcriptomics Organism ComputingMethodologies_COMPUTERGRAPHICS business.industry Deep learning Functional genomics Computer Science Applications Applications of artificial intelligence business TP248.13-248.65 Biotechnology |
| Zdroj: | Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 5762-5790 (2021) Computational and Structural Biotechnology Journal 19 (2021): 5762–5790. doi:10.1016/j.csbj.2021.10.009 info:cnr-pdr/source/autori:Caudai C.; Galizia A.; Geraci F.; Le Pera L.; Morea V.; Salerno E.; Via A.; Colombo T./titolo:AI applications in functional genomics/doi:10.1016%2Fj.csbj.2021.10.009/rivista:Computational and Structural Biotechnology Journal/anno:2021/pagina_da:5762/pagina_a:5790/intervallo_pagine:5762–5790/volume:19 Computational and Structural Biotechnology Journal |
| ISSN: | 2001-0370 |
| Popis: | Graphical abstract 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. |
| Databáze: | OpenAIRE |
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