Protonet: Hierarchical Classification of the Protein Space

• Main Authors: SASSON, Ori, Vaaknin, Avidshay, Fleischer, Hillel, Portugaly, Elon, Bilu, Yonatan, Linial, Nathan, Linial, Michal
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2003
• Subjects: Bioinformatics; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/88; http://dx.doi.org/10.1093/nar/gkg096
• Institution: Singapore Management University

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.