ShopSpell

Modelling Proteasome Dynamics in a Bayesian Framework [Paperback]

$47.99     $54.99   13% Off     (Free Shipping)
100 available
  • Category: Books (Medical)
  • Author:  St?bler, Sabine
  • Author:  St?bler, Sabine
  • ISBN-10:  3658201665
  • ISBN-10:  3658201665
  • ISBN-13:  9783658201661
  • ISBN-13:  9783658201661
  • Publisher:  Springer Spektrum
  • Publisher:  Springer Spektrum
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Apr-2017
  • Pub Date:  01-Apr-2017
  • SKU:  3658201665-11-SPRI
  • SKU:  3658201665-11-SPRI
  • Item ID: 100979032
  • List Price: $54.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Dec 01 to Dec 03
  • Notes: Brand New Book. Order Now.

Sabine St?bler compares different proteasome isoforms and subtypes in terms of their transport and active site-related parameters applying an existing computational model. In a second step, the author extends this model to be able to describe the influence of proteasome inhibitors in in vitro experiments. The computational model, which describes the hydrolysis of short fluorogenic peptides by the 20S proteasome, is calibrated to experimental data from different proteasome isoforms using an approximate Bayesian computation approach. The dynamics of proteasome inhibitors are included into the model in order to demonstrate how to modulate the inhibitors transport parameters for strong or isoform-specific inhibition.

Structure and Function of the Proteasome.- Approaches to Model Proteasome Dynamics.- Comparison of the Dynamics of Proteasome Subtypes.- Inhibitor Influence on the Catalytic Subunits.- Inhibitor Influence on a Compartmentalised Short Fluorogenic Peptide Model .

?

Sabine St?bler works as PhD student in the Computational Physiology Group at the Institute of Biochemistry and Biology, University of Potsdam. Her research focus currently is on developing a novel systems pharmacology model.

Sabine St?bler compares different proteasome isoforms and subtypes in terms of their transport and active site-related parameters applying an existing computational model. In a second step, the author extends this model to be able to describe the influence of proteasome inhibitors in in vitro experiments. The computational model, which describes the hydrolysis of short fluorogenic peptides by the 20S proteasome, is calibrated to experimental data from different proteasome isoforms using an approximate Bayesian computation approach. The dynamics of proteasome inhibitors are included into the model in order to demonstrate how to modulate the inhibitors tranlĂ*