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
Publication
Nucleic Acids Research
Volume
31
Issue
1
First Page
348
Last Page
352
ISSN
0305-1048
Identifier
10.1093/nar/gkg096
Publisher
Oxford
Citation
SASSON, Ori; Vaaknin, Avidshay; Fleischer, Hillel; Portugaly, Elon; Bilu, Yonatan; Linial, Nathan; and Linial, Michal.
Protonet: Hierarchical Classification of the Protein Space. (2003). Nucleic Acids Research. 31, (1), 348-352.
Available at: https://ink.library.smu.edu.sg/sis_research/88
Additional URL
http://dx.doi.org/10.1093/nar/gkg096