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.
Bioinformatics | Computer Sciences
Intelligent Systems and Decision Analytics
Nucleic Acids Research
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. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/88