From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning
We start by highlighting basic concepts of both molecular biology and machine learning. This overview focuses on the key ideas that are required to comprehend the rest of the work, and thus, it does not attempt at providing a comprehensive review. We start with the basis of DNA and RNA, the genet...
| Main Authors: | , , |
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| Format: | info:eu-repo/semantics/doctoralThesis |
| Language: | eng |
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Universidad de Navarra
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10171/65514 |
| _version_ | 1793400472362549248 |
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| author | Serrano-Sanz, G. (Guillermo) Hernaez, M. (Mikel) Guruceaga, E. (Elizabeth) |
| author_facet | Serrano-Sanz, G. (Guillermo) Hernaez, M. (Mikel) Guruceaga, E. (Elizabeth) |
| author_sort | Serrano-Sanz, G. (Guillermo) |
| collection | DSpace |
| description | We start by highlighting basic concepts of both molecular biology and machine learning.
This overview focuses on the key ideas that are required to comprehend the rest of the
work, and thus, it does not attempt at providing a comprehensive review. We start
with the basis of DNA and RNA, the genetic building bricks, until the formation of
the proteins, the final actors of the genetic machinery. We also explore state-of-the-art
technologies to measure those processes along with their limitations. After introducing
the basic biological concepts, we will discuss the basics of machine learning methodologies
and some of the most important models used in recent years to solve many biological
problems. |
| format | info:eu-repo/semantics/doctoralThesis |
| id | oai:dadun.unav.edu:10171-65514 |
| institution | Universidad de Navarra |
| language | eng |
| publishDate | 2023 |
| publisher | Universidad de Navarra |
| record_format | dspace |
| spelling | oai:dadun.unav.edu:10171-655142023-02-27T06:09:22Z From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning Serrano-Sanz, G. (Guillermo) Hernaez, M. (Mikel) Guruceaga, E. (Elizabeth) Materias Investigacion::Ciencias de la vida::Biociencias computacionales Transcriptomics Proteomics Molecular biology Artificial intelligence We start by highlighting basic concepts of both molecular biology and machine learning. This overview focuses on the key ideas that are required to comprehend the rest of the work, and thus, it does not attempt at providing a comprehensive review. We start with the basis of DNA and RNA, the genetic building bricks, until the formation of the proteins, the final actors of the genetic machinery. We also explore state-of-the-art technologies to measure those processes along with their limitations. After introducing the basic biological concepts, we will discuss the basics of machine learning methodologies and some of the most important models used in recent years to solve many biological problems. 2023-02-21T07:38:51Z 2023-02-21T07:38:51Z 2023-02-21 2022-12-20 info:eu-repo/semantics/doctoralThesis https://hdl.handle.net/10171/65514 eng info:eu-repo/semantics/openAccess application/pdf Universidad de Navarra |
| spellingShingle | Materias Investigacion::Ciencias de la vida::Biociencias computacionales Transcriptomics Proteomics Molecular biology Artificial intelligence Serrano-Sanz, G. (Guillermo) Hernaez, M. (Mikel) Guruceaga, E. (Elizabeth) From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning |
| title | From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning |
| title_full | From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning |
| title_fullStr | From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning |
| title_full_unstemmed | From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning |
| title_short | From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning |
| title_sort | from transcriptomics to proteomics: unraveling biological knowledge via machine learning |
| topic | Materias Investigacion::Ciencias de la vida::Biociencias computacionales Transcriptomics Proteomics Molecular biology Artificial intelligence |
| url | https://hdl.handle.net/10171/65514 |
| work_keys_str_mv | AT serranosanzgguillermo fromtranscriptomicstoproteomicsunravelingbiologicalknowledgeviamachinelearning AT hernaezmmikel fromtranscriptomicstoproteomicsunravelingbiologicalknowledgeviamachinelearning AT guruceagaeelizabeth fromtranscriptomicstoproteomicsunravelingbiologicalknowledgeviamachinelearning |