Advances in alternative splicing identification: deep learning and pantranscriptome
In plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate iden...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2023.1232466/full |
| _version_ | 1797681771163156480 |
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| author | Fei Shen Chenyang Hu Chenyang Hu Xin Huang Hao He Deng Yang Jirong Zhao Xiaozeng Yang |
| author_facet | Fei Shen Chenyang Hu Chenyang Hu Xin Huang Hao He Deng Yang Jirong Zhao Xiaozeng Yang |
| author_sort | Fei Shen |
| collection | DOAJ |
| description | In plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate identification of splicing events is a vital step in studying alternative splicing. This article presents the application of alternative splicing algorithms with or without reference genomes in plants, as well as the integration of advanced deep learning techniques for improved detection accuracy. In addition, we also discuss alternative splicing studies in the pan-genomic background and the usefulness of integrated strategies for fully profiling alternative splicing. |
| first_indexed | 2024-03-11T23:50:47Z |
| format | Article |
| id | doaj.art-0505b13ff91c417280a443e60fc8ef47 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-03-11T23:50:47Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-0505b13ff91c417280a443e60fc8ef472023-09-19T07:30:37ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2023-09-011410.3389/fpls.2023.12324661232466Advances in alternative splicing identification: deep learning and pantranscriptomeFei Shen0Chenyang Hu1Chenyang Hu2Xin Huang3Hao He4Deng Yang5Jirong Zhao6Xiaozeng Yang7Institute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, ChinaInstitute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, ChinaShanxi Key Lab of Chinese Jujube, College of Life Science, Yan’an University, Yan’an, Shanxi, ChinaInstitute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, ChinaInstitute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, ChinaInstitute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, ChinaShanxi Key Lab of Chinese Jujube, College of Life Science, Yan’an University, Yan’an, Shanxi, ChinaInstitute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, ChinaIn plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate identification of splicing events is a vital step in studying alternative splicing. This article presents the application of alternative splicing algorithms with or without reference genomes in plants, as well as the integration of advanced deep learning techniques for improved detection accuracy. In addition, we also discuss alternative splicing studies in the pan-genomic background and the usefulness of integrated strategies for fully profiling alternative splicing.https://www.frontiersin.org/articles/10.3389/fpls.2023.1232466/fullalternative splicingRNA-seqIso-seqdetection algorithmdeep learningpantranscriptome |
| spellingShingle | Fei Shen Chenyang Hu Chenyang Hu Xin Huang Hao He Deng Yang Jirong Zhao Xiaozeng Yang Advances in alternative splicing identification: deep learning and pantranscriptome Frontiers in Plant Science alternative splicing RNA-seq Iso-seq detection algorithm deep learning pantranscriptome |
| title | Advances in alternative splicing identification: deep learning and pantranscriptome |
| title_full | Advances in alternative splicing identification: deep learning and pantranscriptome |
| title_fullStr | Advances in alternative splicing identification: deep learning and pantranscriptome |
| title_full_unstemmed | Advances in alternative splicing identification: deep learning and pantranscriptome |
| title_short | Advances in alternative splicing identification: deep learning and pantranscriptome |
| title_sort | advances in alternative splicing identification deep learning and pantranscriptome |
| topic | alternative splicing RNA-seq Iso-seq detection algorithm deep learning pantranscriptome |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1232466/full |
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