|◇ 授業内容 Course description ：
||Introduction to Graphs/Networks, Different network models, Properties of Protein-Protein Interaction Networks, Different centrality measures of nodes, Protein Function prediction using network concepts, Application of network concepts in DNA sequencing, Line graphs.
Concept and types of metric, Hierarchical Clustering, Finding clusters in undirected simple graphs: application to protein complex detection.
Introduction to KNApSAcK database, Metabolic Reaction system as ordinary differential equations, Metabolic Reaction system as stochastic process.
Metabolic network and stoichiometric matrix, Information contained in stoichiometric matrix, Elementary flux modes and extreme pathways.
Graph spectral analysis/Graph spectral clustering and its application to metabolic networks.
Normalization procedures for gene expression data, Tests for differential expression of genes, Multiple testing and FDR, Reverse Engineering of genetic networks.
Finding Biclusters in Bipartite Graphs, Properties of transcriptional/gene regulatory networks, Introduction to software package Expander.
Introduction to signaling pathways, Selected biological processes: Glycolytic oscillations, sustained oscillation in signaling cascades.
Structural Similarity based Multifaceted Analysis of Metabolites.