Machine learning applications on biological data
Machine learning has been used frequently for biological studies with applications of prediction, discovery and classification. With the flux of multiple types of largescale data, the development of machine learning methods, especially the application of deep learning approaches, has become more...
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| Format: | Thesis-Master by Research |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/159232 |
| _version_ | 1826114903311646720 |
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| author | Xu, Ying |
| author2 | Lin Weisi |
| author_facet | Lin Weisi Xu, Ying |
| author_sort | Xu, Ying |
| collection | NTU |
| description | Machine learning has been used frequently for biological studies with applications
of prediction, discovery and classification. With the flux of multiple types of largescale
data, the development of machine learning methods, especially the application
of deep learning approaches, has become more promising.
This thesis studies machine learning applications on ageing research as a stochastic
model. We review the exploration of relationships between certain types of DNA
repair and ageing, the function of age-related proteins in molecular pathways and
relationships between ageing and apoptosis. The research shows how machine
learning algorithms can be further improved coupled with state-of-the-art molecular
analysis technologies.
Furthermore, we build a deep neural network for plant video classification for a
typical application of pesticide spraying drone. Plants can act differently under
different growth stage, soil fertility, availability of water, climate, diseases or pests.
Video classification of plants according to the waving feature is important for the
pilotless aerial vehicles to spray pesticides selectively and improve automation of
precision agriculture. |
| first_indexed | 2024-10-01T03:46:48Z |
| format | Thesis-Master by Research |
| id | ntu-10356/159232 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:46:48Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1592322022-06-20T07:47:13Z Machine learning applications on biological data Xu, Ying Lin Weisi School of Computer Science and Engineering WSLin@ntu.edu.sg Engineering::Computer science and engineering Engineering::Bioengineering Machine learning has been used frequently for biological studies with applications of prediction, discovery and classification. With the flux of multiple types of largescale data, the development of machine learning methods, especially the application of deep learning approaches, has become more promising. This thesis studies machine learning applications on ageing research as a stochastic model. We review the exploration of relationships between certain types of DNA repair and ageing, the function of age-related proteins in molecular pathways and relationships between ageing and apoptosis. The research shows how machine learning algorithms can be further improved coupled with state-of-the-art molecular analysis technologies. Furthermore, we build a deep neural network for plant video classification for a typical application of pesticide spraying drone. Plants can act differently under different growth stage, soil fertility, availability of water, climate, diseases or pests. Video classification of plants according to the waving feature is important for the pilotless aerial vehicles to spray pesticides selectively and improve automation of precision agriculture. Master of Engineering 2022-06-20T07:47:13Z 2022-06-20T07:47:13Z 2022 Thesis-Master by Research Xu, Y. (2022). Machine learning applications on biological data. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159232 https://hdl.handle.net/10356/159232 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering Engineering::Bioengineering Xu, Ying Machine learning applications on biological data |
| title | Machine learning applications on biological data |
| title_full | Machine learning applications on biological data |
| title_fullStr | Machine learning applications on biological data |
| title_full_unstemmed | Machine learning applications on biological data |
| title_short | Machine learning applications on biological data |
| title_sort | machine learning applications on biological data |
| topic | Engineering::Computer science and engineering Engineering::Bioengineering |
| url | https://hdl.handle.net/10356/159232 |
| work_keys_str_mv | AT xuying machinelearningapplicationsonbiologicaldata |