Machine Learning Research Group

We are working to develop novel algorithms for use in molecular biology and drug discovery. Our main areas of interest include:

Research Topics

Privacy-preserving search in chemical compound databases
Comprehensive analysis of millions of ligand-binding pockets based on efficient all pairs similarity search
Fast clustering of massive short reads by multiple sorting
Machine learning methods for activity recognition from biomedical sensor data

click for full size(262KB)

Team Member

Koji Tsuda
Senior Research Scientist E-mail
Koji Tsuda
Key Words

Machine learning, Kernel methods, Protein networks, Structured data

David Du Verle
Key Words

machine learning, gene expression analysis, time series analysis, gene regulatory network inference

Papers List

  • J. Ito, Y. Tabei, K. Shimizu, K. Tomii and K. Tsuda: "PDB-scale Analysis of Known and Putative Ligand-binding Sites with Structural Sketches", Proteins, 80:747-763, (2012).
  • Y. Tabei and K. Tsuda. SketchSort: "Fast All Pairs Similarity Search for Large Databases of Molecular Fingerprints.", Molecular Informatics, 30(9):801-807, 2011.
  • K. Shimizu and K. Tsuda. SlideSort: "All Pairs Similarity Search for Short Reads.", Bioinformatics, 27(4):464-470, (2011).
  • E. Georgii, K. Tsuda and B. Schoelkopf: "Multi-way Set Enumeration in Weight Tensors", Machine Learning, 82(2):123-155, (2011).
page top

Site Policy (c) Computational Biology Research Center, AIST, 2001-2012 All Rights Reserved.