SecStAnT: a Secondary Structure Analysis Tool for data selection, statistics and models building (Articolo in rivista)

Type
Label
  • SecStAnT: a Secondary Structure Analysis Tool for data selection, statistics and models building (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1093/bioinformatics/btt586 (literal)
Alternative label
  • G. Maccari, [ 1 ] ; G. L. B. Spampinato [ 2,3,4 ] ; V. Tozzini, [ 2,3 ] (2014)
    SecStAnT: a Secondary Structure Analysis Tool for data selection, statistics and models building
    in Bioinformatics (Oxf., Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • G. Maccari, [ 1 ] ; G. L. B. Spampinato [ 2,3,4 ] ; V. Tozzini, [ 2,3 ] (literal)
Pagina inizio
  • 668 (literal)
Pagina fine
  • 674 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 30 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • [ 1 ] Ist Italiano Tecnol, Ctr Nanotechnol & Innovat NEST, I-56127 Pisa, Italy [ 2 ] NEST, Ist Nanosci, CNR, I-56127 Pisa, Italy [ 3 ] Scuola Normale Super Pisa, I-56127 Pisa, Italy [ 4 ] Univ Pisa, Dipartimento Fis E Fermi, I-56127 Pisa, Italy (literal)
Titolo
  • SecStAnT: a Secondary Structure Analysis Tool for data selection, statistics and models building (literal)
Abstract
  • Motivation: Atomistic or coarse grained (CG) potentials derived from statistical distributions of internal variables have recently become popular due to the need of simplified interactions for reaching larger scales in simulations or more efficient conformational space sampling. However, the process of parameterization of accurate and predictive statistics-based force fields requires a huge amount of work and is prone to the introduction of bias and errors. Results: This article introduces SecStAnT, a software for the creation and analysis of protein structural datasets with user-defined primary/secondary structure composition, with a particular focus on the CG representation. In addition, the possibility of managing different resolutions and the primary/secondary structure selectivity allow addressing the mapping-backmapping of atomistic to CG representation and study the secondary to primary structure relations. Sample datasets and distributions are reported, including interpretation of structural features. (literal)
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