Protein structure is complex trajectory in 3D space and it can be ab-stracted into a polygonal curve. Capturing structural properties from the Cartesian coordinates of thousands of atoms is an important step in performing structural analysis such as similarity detection and defining patterns. The objective of this research is to investigate the potential use of some knot theoretic quantities such as self-linking, R30 invariants and HEO vector for structural Bioinformatics applications. The work presented suggests that self-linking (writhing) can be used to identify a-helices. A revised sliding window approach together with 2 curve simplification methods were employed in the optimal window analysis to capture regions that maximize or mini-mize self-linking properties in a protein's backbone trajectory. The accuracy of this method is significant although insufficient to be used for domain boundary identification. Most interestingly, the topo-logical properties of adjacent protein domains are significantly larger than for domain that are not adjacent within a gene. This experi-mental result suggests that proteins tend to evolve contiguous domains with polarized topological properties.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 5722960-n
Quantité disponible : Plus de 20 disponibles
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
Paperback or Softback. Etat : New. Assessment of the Use of Topological Quantities in Structural Bioinformatics. Book. N° de réf. du vendeur BBS-9783639045703
Quantité disponible : 5 disponible(s)
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9783639045703
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 5722960
Quantité disponible : Plus de 20 disponibles
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur LU-9783639045703
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9783639045703
Quantité disponible : Plus de 20 disponibles
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur 6666-IUK-9783639045703
Quantité disponible : 10 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 5722960-n
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 5722960
Quantité disponible : Plus de 20 disponibles
Vendeur : moluna, Greven, Allemagne
Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Lu JiantaoJiantao Lu has received a M.Sc. degree in Educational Technology and a B.Sc. degree in Electronic Engineering in China. He has been working on Bioinformatics as a Ph.D. student in the faculty of computer science at Dalhousi. N° de réf. du vendeur 4952338
Quantité disponible : Plus de 20 disponibles