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Prediction of mRNA Subcellular Localization Using Deep Learning and Investigating Optical Implementation Feasibility

Shahbakhsh, Aref | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57132 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Koohi, Somayyeh
  7. Abstract:
  8. Proper positioning of messenger RNA helps to diagnose diseases such as cancer, Alzheimer’s, and also to make drugs for treatment; Therefore, predicting the location of messenger RNA in the cell with the aim of determining the type of proteins formed from a messenger RNA sequence is very important. Although experimental methods such as complex laboratory processes can provide accurate information about the intracellular localization of messenger RNA, however, the computational overhead, including time, memory and power consumption, increases the need to design accurate, fast and low-cost tools more than ever. Nowday, deep neural networks have shown significant performance in the field of biological data processing compared to traditional tools and laboratory methods, however, existing architectures always suffer from challenges such as reducing accuracy, processing speed, increasing memory consumption, and power consumption. They take. On the other hand, optical processing platforms can significantly reduce the overhead and computing costs of deep neural networks by using the speed of light and its parallelization capability. Therefore, in this research, we designed an intracellular localization tool for RNA and We use deep neural networks with the ability to implement optical messengers
  9. Keywords:
  10. Deep Learning ; Optical Neural Networks ; Localization ; Optical Artificial Neural Networks ; Messenger RNAs

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