文档介绍：衛資所生物資訊組陳俊宇
April 07, 03
graph
graph
node
edge
Chromosome
gene
positional correlations
Pathway
enzyme
functional correlations
Gene expression
gene
coexpressed
Protein interaction
protein
protein-protein interaction
Protein structure
protein
3D structural similarity
What questions they want to answer?
Ci: correlated gene cluster
(correlated cluster)
hi: hyperedge
To extract a set of correlated genes with respect to multiple biological features.
Provide biological information to classify genes.
Method
Clustering of hyperedges!!
Input datasets:
graph G = {G1, …, Gn}
hyperedges H = {h1, …, hm}
Distance between hyperedges:
correlated gene clusters
genome dataset (G1: 4,396 nodes and 4,396 edges)
pathway dataset (G2: 761 nodes and 1,223 edges)
structure similarity dataset (G3: 538 nodes and 3,823 edges)
917 hyperedges
threshold parameters p1 = 2, p2 = 3, p3 = 0
Screening the two-hybrid protein-protein interaction dataset. (yeast protein interaction)
Compared this dataset with the following datasets:
coexpression dataset
pathway dataset
genome dataset
If an interaction or a relation is also observed