title: ProtoNet: hierarchical classification of the protein space.
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.
authors.affiliation: School of Computer Science and Engineering, Institute of Life Sciences, The Hebrew University, Jerusalem 91904, Israel.
authors.forename: Ori
authors.initials: O
authors.lastname: Sasson
authors.forename: Avishay
authors.initials: A
authors.lastname: Vaaknin
authors.forename: Hillel
authors.initials: H
authors.lastname: Fleischer
authors.forename: Elon
authors.initials: E
authors.lastname: Portugaly
authors.forename: Yonatan
authors.initials: Y
authors.lastname: Bilu
authors.forename: Nathan
authors.initials: N
authors.lastname: Linial
authors.forename: Michal
authors.initials: M
authors.lastname: Linial
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D030562:Databases, Protein; D016247:Information Storage and Retrieval; D020407:Internet; D011506:Proteins / Q000737:chemistry / Q000145:classification* / Q000502:physiology
chemical_list: D011506:Proteins