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