Multiple Alignment Through SecondaryStructure Information (Articolo in rivista)

Type
Label
  • Multiple Alignment Through SecondaryStructure Information (Articolo in rivista) (literal)
Anno
  • 2005-01-01T00:00:00+01:00 (literal)
Alternative label
  • Armano G., Milanesi L. and A. Orro. (2005)
    Multiple Alignment Through SecondaryStructure Information
    in IEEE transactions on nanotechnology
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Armano G., Milanesi L. and A. Orro. (literal)
Pagina inizio
  • 207 (literal)
Pagina fine
  • 211 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 4 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • G. Armano and A. Orro -Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, Cagliari I-09123, Italy L. Milanesi -Institute for Biomedical Technologies (ITB), CNR, Segrate I-20090, Milano, Italy. (literal)
Titolo
  • Multiple Alignment Through SecondaryStructure Information (literal)
Abstract
  • Abstract—It is well known that protein secondary-structure information can help the process of performing multiple alignment, in particular when the amount of similarity among the involved sequences moves toward the “twilight zone” (less than 30% of pairwise similarity). In this paper, a multiple alignment algorithm is presented, explicitly designed for exploiting any available secondary- structure information. A layered architecture with two interacting levels has been defined for dealing with both primaryand secondary-structure information of target sequences. Secondary structure (either available or predicted by resorting to a technique based on multiple experts) is used to calculate an initial alignment at the secondary level, to be arranged by locally scoped operators devised to refine the alignment at the primary level. Aimed at evaluating the impact of secondary information on the quality of alignments, in particular alignments with a low degree of similarity, the technique has been implemented and assessed on relevant test cases. (literal)
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