Rapid detection, classification and accurate alignment of up to a million or more related protein sequences
AUTOR(ES)
Neuwald, Andrew F.
FONTE
Oxford University Press
RESUMO
Motivation: The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2732367Documentos Relacionados
- ProtoNet 4.0: A hierarchical classification of one million protein sequences
- Rapid Method for Detection, Identification, and Susceptibility Testing of Enteric Pathogens
- ONE HUNDRED MILLION GUINEA PIGS: AND TEN MILLION MORE
- Discovering active motifs in sets of related protein sequences and using them for classification.
- Application of immunoperoxidase staining to more rapid detection and identification of rubella virus isolates.
