Modelling proteasome dynamics in a Bayesian framework

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Bibliographic Details
Main Author: Stübler, Sabine, (Author)
Format: eBook
Language: English
Published: Wiesbaden : Springer Spektrum, ©2017.
Series: BestMasters.
Subjects:
ISBN: 9783658201678
9783658201661
Physical Description: 1 online resource : illustrations

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040 |a YDX  |b eng  |e pn  |c YDX  |d N$T  |d GW5XE  |d EBLCP  |d IOG  |d OCLCF  |d UAB  |d MERER  |d SNK  |d OCLCQ  |d VT2  |d U3W  |d OCLCQ  |d KSU  |d ESU  |d WYU  |d LVT  |d OCLCQ  |d CAUOI  |d MERUC  |d UKAHL  |d OCLCQ 
020 |a 9783658201678  |q (electronic bk.) 
020 |z 9783658201661 
035 |a (OCoLC)1013820500  |z (OCoLC)1021251324 
100 1 |a Stübler, Sabine,  |e author. 
245 1 0 |a Modelling proteasome dynamics in a Bayesian framework /  |c Sabine Stübler. 
260 |a Wiesbaden :  |b Springer Spektrum,  |c ©2017. 
300 |a 1 online resource :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a BestMasters 
504 |a Includes bibliographical references and index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 8 |a Annotation  |b Sabine Stubler 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 inhibitor's transport parameters for strong or isoform-specific inhibition. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Proteomics. 
650 0 |a Proteolytic enzymes. 
650 0 |a Bayesian statistical decision theory. 
650 0 |a Immunology. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |z 3658201665  |z 9783658201661  |w (OCoLC)1007921585 
830 0 |a BestMasters. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-658-20167-8  |y Plný text 
992 |c NTK-SpringerBLS 
999 |c 97658  |d 97658