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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.

  • RNA modification analysis using nanopore sequencer

    RNA modification analysis using nanopore sequencer

  • Development of RNA modification analysis algorithm using 1D-CNN and one-class classification method

    Development of RNA modification analysis algorithm using 1D-CNN and one-class classification method

  • RNA Sequencing and Whole genome sequencing using Hadoop

    RNA Sequencing and Whole genome sequencing using Hadoop

Member

  • Hiroki UEDA
  • Specialized field : Computational Biology, Cancer Genomics, Machine Learning

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