Advanced Data Science
Ueda Laboratory
Biological Big Data to Knowledge, using Data Science
Biological Data Science
With the advancement of sequencing technologies, it has become a challenging task to process large volumes of data with conventional methods. In order to extract knowledge from biological big data, (ex. Multi-omics data) it is necessary to incorporate the latest Data Science technology, such as cloud computing and machine learning. We are developing cloud based Single Cell NGS analysis pipeline using Hadoop/Spark, (cloud computing framework) and developing the method to identify RNA modifications using deep learning method.
Our research include following:
- (1) Epitranscriptome (RNA modifications) analysis using nanopore sequencer
- (2) Cancer genomics
- (3) Proteomics and post translational modification
- (4) Single Cell genomics
Also, from this fiscal year, the RCAST Cross-disciplinary Data/AI initiative to utilize data from each field of RCAST using cloud/AI technology to be launched, and we will be taking the main role in implementing that project.
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RNA modification analysis using nanopore sequencer
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Development of RNA modification analysis algorithm using 1D-CNN and one-class classification method
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RNA Sequencing and Whole genome sequencing using Hadoop
Member
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- Project Lecturer
Hiroki UEDA
Specialized field : Computational Biology, Cancer Genomics, Machine Learning - Project Lecturer
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