Title

Protonet: Hierarchical Classification of the Protein Space

Publication Type

Journal Article

Publication Date

2003

Abstract

The ProtoNet site provides an automatic hierarchical clustering of the SWISS-PROT protein database. The clustering is based on an all-against-all BLAST similarity search. The similarities' E-score is used to perform a continuous bottom-up clustering process by applying alternative rules for merging clusters. The outcome of this clustering process is a classification of the input proteins into a hierarchy of clusters of varying degrees of granularity. ProtoNet (version 1.3) is accessible in the form of an interactive web site at http://www.protonet.cs.huji.ac.il. ProtoNet provides navigation tools for monitoring the clustering process with a vertical and horizontal view. Each cluster at any level of the hierarchy is assigned with a statistical index, indicating the level of purity based on biological keywords such as those provided by SWISS-PROT and InterPro. ProtoNet can be used for function prediction, for defining superfamilies and subfamilies and for large-scale protein annotation purposes.

Discipline

Bioinformatics | Computer Sciences

Research Areas

Intelligent Systems and Decision Analytics

Publication

Nucleic Acids Research

Volume

31

Issue

1

First Page

348

Last Page

352

ISSN

0305-1048

Identifier

10.1093/nar/gkg096

Publisher

Oxford

Additional URL

http://dx.doi.org/10.1093/nar/gkg096