ProtoNet: hierarchical classification of the protein space
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چکیده
منابع مشابه
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...
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...
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 کاملPredicting 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 کاملA Map of the Protein Space: An Automatic Hierarchical Classification of all Protein Sequences
We investigate the space of all protein sequences. We combine the standard measures of similarity (SW, FASTA, BLAST), to associate with each sequence an exhaustive list of neighboring sequences. These lists induce a (weighted directed) graph whose vertices are the sequences. The weight of an edge connecting two sequences represents their degree of similarity. This graph encodes much of the fund...
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ژورنال
عنوان ژورنال: Nucleic Acids Research
سال: 2003
ISSN: 1362-4962
DOI: 10.1093/nar/gkg096