ProtoNet: Hierarchical classification of the protein space

Ori Sasson, Avishay Vaaknin, Hillel Fleischer, Elon Portugaly, Yonatan Bilu, Nathan Linial, Michal Linial*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

65 Scopus citations

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.

Original languageAmerican English
Pages (from-to)348-352
Number of pages5
JournalNucleic Acids Research
Volume31
Issue number1
DOIs
StatePublished - 1 Jan 2003

Bibliographical note

Funding Information:
This work was supported by the Israeli Ministry of Defense, the Israeli Ministry of Science and by the Horowitz Foundation.

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