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Biomedical Data Science Lab.
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Kengo Sato

Kengo Sato

Professor

Tokyo Denki University, Japan

Kengo Sato is a professor at Tokyo Denki University School of System Design and Technology, Japan. He received his Ph.D. in Computer Science from Keio University, Japan, in 2003. He was awarded the Oxford Journals JSBi Prize in 2008 and the IPSJ Yamashita SIG Research Award in 2012. His research interests include bioinformatics, machine learning and life sciences. He develops innovative algorithms for sequence analysis and RNA informatics.

Latest

  • Direct inference of base-pairing probabilities with neural networks improves prediction of RNA secondary structures with pseudoknots
  • Integer programming for selecting set of informative markers in paternity inference
  • Biomedical Data Science Lab has launched.
  • Prediction of RNA secondary structure including pseudoknots for long sequences
  • A max-margin model for predicting residue-base contacts in protein-RNA interactions
  • A web server for designing molecular switches composed of two interacting RNAs
  • RNA secondary structure prediction using deep learning with thermodynamic integration
  • An improved de novo genome assembly of the common marmoset genome yields improved contiguity and increased mapping rates of sequence data
  • Efficient generation of Knock-in/Knock-out marmoset embryo via CRISPR/Cas9 gene editing
  • A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model

© 2022 Biomedical Data Science Lab. This work is licensed under CC BY NC ND 4.0

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