Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases
Micro-RNAs (miRNAs) are short (∼21 nt) non-coding RNAs that regulate gene expression through the degradation or translational repression of mRNAs. Accumulating evidence points to a role of miRNA regulation in the pathogenesis of a wide range of neurodegenerative (ND) diseases such as, for example, A...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Molecular Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnmol.2022.914830/full |
| _version_ | 1798003418345766912 |
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| author | Lucile Mégret Cloé Mendoza Maialen Arrieta Lobo Emmanuel Brouillet Thi-Thanh-Yen Nguyen Olivier Bouaziz Antoine Chambaz Christian Néri |
| author_facet | Lucile Mégret Cloé Mendoza Maialen Arrieta Lobo Emmanuel Brouillet Thi-Thanh-Yen Nguyen Olivier Bouaziz Antoine Chambaz Christian Néri |
| author_sort | Lucile Mégret |
| collection | DOAJ |
| description | Micro-RNAs (miRNAs) are short (∼21 nt) non-coding RNAs that regulate gene expression through the degradation or translational repression of mRNAs. Accumulating evidence points to a role of miRNA regulation in the pathogenesis of a wide range of neurodegenerative (ND) diseases such as, for example, Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and Huntington disease (HD). Several systems level studies aimed to explore the role of miRNA regulation in NDs, but these studies remain challenging. Part of the problem may be related to the lack of sufficiently rich or homogeneous data, such as time series or cell-type-specific data obtained in model systems or human biosamples, to account for context dependency. Part of the problem may also be related to the methodological challenges associated with the accurate system-level modeling of miRNA and mRNA data. Here, we critically review the main families of machine learning methods used to analyze expression data, highlighting the added value of using shape-analysis concepts as a solution for precisely modeling highly dimensional miRNA and mRNA data such as the ones obtained in the study of the HD process, and elaborating on the potential of these concepts and methods for modeling complex omics data. |
| first_indexed | 2024-04-11T12:07:16Z |
| format | Article |
| id | doaj.art-48b3f5790cc3413da2eb116f53568786 |
| institution | Directory Open Access Journal |
| issn | 1662-5099 |
| language | English |
| last_indexed | 2024-04-11T12:07:16Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Molecular Neuroscience |
| spelling | doaj.art-48b3f5790cc3413da2eb116f535687862022-12-22T04:24:42ZengFrontiers Media S.A.Frontiers in Molecular Neuroscience1662-50992022-09-011510.3389/fnmol.2022.914830914830Precision machine learning to understand micro-RNA regulation in neurodegenerative diseasesLucile Mégret0Cloé Mendoza1Maialen Arrieta Lobo2Emmanuel Brouillet3Thi-Thanh-Yen Nguyen4Olivier Bouaziz5Antoine Chambaz6Christian Néri7Sorbonne Université, Centre National de la Recherche Scientifique UMR 8256, Paris, FranceSorbonne Université, Centre National de la Recherche Scientifique UMR 8256, Paris, FranceSorbonne Université, Centre National de la Recherche Scientifique UMR 8256, Paris, FranceSorbonne Université, Centre National de la Recherche Scientifique UMR 8256, Paris, FranceUniversité Paris Cité, MAP5 (Centre National de la Recherche Scientifique UMR 8145), Paris, FranceUniversité Paris Cité, MAP5 (Centre National de la Recherche Scientifique UMR 8145), Paris, FranceUniversité Paris Cité, MAP5 (Centre National de la Recherche Scientifique UMR 8145), Paris, FranceSorbonne Université, Centre National de la Recherche Scientifique UMR 8256, Paris, FranceMicro-RNAs (miRNAs) are short (∼21 nt) non-coding RNAs that regulate gene expression through the degradation or translational repression of mRNAs. Accumulating evidence points to a role of miRNA regulation in the pathogenesis of a wide range of neurodegenerative (ND) diseases such as, for example, Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and Huntington disease (HD). Several systems level studies aimed to explore the role of miRNA regulation in NDs, but these studies remain challenging. Part of the problem may be related to the lack of sufficiently rich or homogeneous data, such as time series or cell-type-specific data obtained in model systems or human biosamples, to account for context dependency. Part of the problem may also be related to the methodological challenges associated with the accurate system-level modeling of miRNA and mRNA data. Here, we critically review the main families of machine learning methods used to analyze expression data, highlighting the added value of using shape-analysis concepts as a solution for precisely modeling highly dimensional miRNA and mRNA data such as the ones obtained in the study of the HD process, and elaborating on the potential of these concepts and methods for modeling complex omics data.https://www.frontiersin.org/articles/10.3389/fnmol.2022.914830/fullneurodegenerative diseasemiRNA regulationcomplex RNA-seq datamachine learningprecision analysisshape analysis |
| spellingShingle | Lucile Mégret Cloé Mendoza Maialen Arrieta Lobo Emmanuel Brouillet Thi-Thanh-Yen Nguyen Olivier Bouaziz Antoine Chambaz Christian Néri Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases Frontiers in Molecular Neuroscience neurodegenerative disease miRNA regulation complex RNA-seq data machine learning precision analysis shape analysis |
| title | Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases |
| title_full | Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases |
| title_fullStr | Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases |
| title_full_unstemmed | Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases |
| title_short | Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases |
| title_sort | precision machine learning to understand micro rna regulation in neurodegenerative diseases |
| topic | neurodegenerative disease miRNA regulation complex RNA-seq data machine learning precision analysis shape analysis |
| url | https://www.frontiersin.org/articles/10.3389/fnmol.2022.914830/full |
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