Predicting fold novelty based on ProtoNet hierarchical classification
نویسندگان
چکیده
منابع مشابه
Predicting fold novelty based on ProtoNet hierarchical classification
MOTIVATION Structural genomics projects aim to solve a large number of protein structures with the ultimate objective of representing the entire protein space. The computational challenge is to identify and prioritize a small set of proteins with new, currently unknown, superfamilies or folds. RESULTS We develop a method that assigns each protein a likelihood of it belonging to a new, yet und...
متن کاملProtoNet: 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...
متن کاملProtoNet 4.0: A hierarchical classification of one million protein sequences
ProtoNet is an automatic hierarchical classification of the protein sequence space. In 2004, the ProtoNet (version 4.0) presents the analysis of over one million proteins merged from SwissProt and TrEMBL databases. In addition to rich visualization and analysis tools to navigate the clustering hierarchy, we incorporated several improvements that allow a simplified view of the scaffold of the pr...
متن کاملTarget selection for structural genomics based on ProtoNet classification
Motivation: Structural genomics projects aim to solve a large number of protein structures to eventually represent the entire protein space. To this end it is necessary to increase the rate at which new families, superfamilies and folds are discovered. To facilitate that, strategies to improve the selection of targets for structural determination are needed. An important component in the design...
متن کاملProtoNet : Navigating the Hierarchical Clustering of the Protein Space
The ProtoNet site provides an automatic hierarchical clustering of the protein space. The clustering is based on an all-against-all BLAST similarity test. With this similarity measure we proceed 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...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2004
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/bti135