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From experimental, structural probability distributions to the theoretical causality analysis of molecular changes

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Języki publikacji
EN
Abstrakty
EN
A brief overview of causality analysis (CA) methods applied to MD simulations data for model biomolecular systems is presented. A CausalMD application for postprocessing of MD data was designed and implemented. MD simulations of two model systems, porphycene (ab initio MD) and HIV-1 protease (coarse-grained MD) were carried out and analyzed. Granger’s causality methodology based on a Multivariate Autoregressive (MVAR) formalism, followed by the Directed Transfer Function (DTF) analysis was applied. A novel approach based on the descriptors of local structure was also presented and prelim- inary results were reported. Casuality analyses are required for a better understanding of biomolecular functioning mechanisms. In particular, such analyses can link physics-based structural dynamics with functions inferred from molecular evolution processes. Current limitations and future developments of the presented methodologies are indicated.
Rocznik
Strony
257--276
Opis fizyczny
Bibliogr. 57 poz., rys., tab., wykr.
Twórcy
autor
autor
autor
autor
  • Bioinformatics Laboratory, Mossakowski Medical Research Centre Polish Academy of Sciences Pawińskiego 5, 02-106 Warsaw, Poland, lesyng@icm.edu.pl
Bibliografia
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPBF-0001-0005
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