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PMID: 12520020 Published · ppublish English Journal Article

ProtoNet: hierarchical classification of the protein space.

Nucleic acids research ·Vol. 31 ·No. 1 ·2003-01-01 ·Pages 348-52

Sasson O, Vaaknin A, Fleischer H, Portugaly E, Bilu Y, Linial N, Linial M

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.

MeSH Terms
Animals Cluster Analysis Databases, Protein Information Storage and Retrieval Internet Proteins/chemistry,classification,physiology
Chemicals
Proteins
Authors & Affiliations
7 authors, click to expand affiliations / ORCID
Sasson Ori
School of Computer Science and Engineering, Institute of Life Sciences, The Hebrew University, Jerusalem 91904, Israel.
Vaaknin Avishay
Fleischer Hillel
Portugaly Elon
Bilu Yonatan
Linial Nathan
Linial Michal
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18 references, click to expand
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Article Info
Journal
Nucleic acids research
Abbr.
Nucleic Acids Res
ISSN
1362-4962
Published
2003-01-01
Pages
348-52
Language
English
Region
England
NLM ID
0411011
PMCID
PMC165543
Subset
IM
Analysis Services
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