Computational Biology Research Center[CBRC]
Advanced Industrial Science and Technology[AIST]| Key Word Search |
|
- Top
- กไ
- Introduction
- กไ
- Research
- กไ
- Research Subjects
Research Subjects
-
Genome Informatics
-
Team
Outline
Genome informatics aims to develop: rapid and accurate RNA sequence information analysis technologies based on secondary structure, sequence motif extraction for the discovery of transcription regulatory sites, and software tools for RNA and promoter analysis. The applications of these technologies include the analysis of transcription control mechanisms, prediction of the influence of genetic polymorphisms, and the discovery of novel functional RNA.
Theme
- Information analysis of functional RNAs
- Information analysis of transcriptional regulation
Aim
- Discovery and functional prediction of novel functional RNAs
- Multifaceted prediction of transcriptional regulation and elucidation of mechanism
Elemental technology
- Alignment and search of RNA sequence
- Analysis of promoter sequences
- Prediction of intracellular localization
-
-
Molecular Informatics
-
Team
Outline
Molecular Informatics seeks to integrate molecular design strategies with extant technologies such as protein structure/function prediction and molecular simulation in an effort to develop accurate drug discovery support tools for target proteins and degenerative disease-related peptides/carbohydrate chains. It looks to develop methods for predicting the complex structures of protein-protein or protein-other biological molecule (nucleic acid, compound, or carbohydrate chain) by large-scale computation.
Theme
- Structure prediction of protein-protein complexes
- Structure-based virtual screening for drug discovery
Aim
- Development of structure prediction for flexible protein complexes
- Structure-based virtual screening for drug discovery ก๕ focused library design
Elemental technology
- Accurate protein structure prediction
- Docking simulation
-
-
Cellular Informatics
-
Team
Outline
Cellular Informatics focuses on intracellular networks including gene expression, metabolism, and signal transduction using an engineering approach. It seeks to establish a comprehensive human cell database and develop an integrative and global cellular information analysis environment combining information on cell morphology, function, and transdifferentiation with gene expression data. Enabling the prediction of intracellular networks including biological molecules with unknown functions, we develop technologies that support the discovery of novel drug targets and the prediction of adverse drug reactions.
Theme
- Analysis of gene expression information
- Biological network information analysis
Aim
- Prediction of gene expression modules and networks related to cell differentiation
- Prediction of disease-related networks
- Prediction of adverse drug reactions
Elemental technology
- Gene expression module search
- Network structure prediction
- Network dynamics analysis
-
-
Integration of Information Platform
-
Team
Outline
This is aimed at the establishment of a bioinformatics information platform that seamlessly integrates internal and external databases and software using current information technologies.
Combines the latest mathematical methods and bioinformatics analysis technologies using large-scale computation on the order of several thousand processors to develop practicable systems.Aim
- Development of a pipeline combining elemental technologies of bioinformatics
- Realization of an environment that can be used safety and seamlessly by combining intellectual basis including external bioinformatics databases
- Realization of various services corresponding to user's needs by a simple operation
Cooperation
- Related units in AIST
-