Machine learning applications on biological data

• المؤلف الرئيسي: Xu, Ying
• مؤلفون آخرون: Lin Weisi
• التنسيق: Thesis-Master by Research
• اللغة: English
• منشور في: Nanyang Technological University 2022
• الموضوعات: Engineering::Computer science and engineering; Engineering::Bioengineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/159232

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.