Self-organizing trees for visualizing protein dataset

Clustering and visualizing multidimensional or structured data are important tasks for data analysis, especially in bioinformatics. Self-organizing models are often used to address both of these issues. In this paper we introduce a hierarchical and topological visualization technique called Self-org...

Full description

Saved in:
Bibliographic Details
Main Authors: Nhat-Quang Doan, Azzag, Hanane, Lebbah, Mustapha, Santini, Guillaume
Format: Conference Proceeding
Language:English
Subjects:
Clustering
Data visualization
hierarchical trees
Laplace equations
protein data
protein domains
Proteins
Prototypes
self-organizing map
Three-dimensional displays
Topology
Vectors
visualization
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Clustering and visualizing multidimensional or structured data are important tasks for data analysis, especially in bioinformatics. Self-organizing models are often used to address both of these issues. In this paper we introduce a hierarchical and topological visualization technique called Self-organizing Trees (SoT) which is able to represent data in hierarchical and topological structure. The experiment is conducted on a real-world protein data set.
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2013.6707001