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Experimental design trade-offs for gene regulatory network inference: an in silico study of the yeast Saccharomyces cerevisiae cell cycle
Markdahl, Johan; Colombo, Nicolo; Thunberg, Johan et al.
2017In Proceedings of the 56th IEEE Conference on Decision and Control
Peer reviewed
 

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Keywords :
gene regulatory network; network inference; sampled systems; time-series; yeast; Saccharomyces cerevisiae
Abstract :
[en] Time-series of high throughput gene sequencing data intended for gene regulatory network (GRN) inference are often short due to the high costs of sampling cell systems. Moreover, experimentalists lack a set of quantitative guidelines that prescribe the minimal number of samples required to infer a reliable GRN model. We study the temporal resolution of data vs.quality of GRN inference in order to ultimately overcome this deficit. The evolution of a Markovian jump process model for the Ras/cAMP/PKA pathway of proteins and metabolites in the G1 phase of the Saccharomyces cerevisiae cell cycle is sampled at a number of different rates. For each time-series we infer a linear regression model of the GRN using the LASSO method. The inferred network topology is evaluated in terms of the area under the precision-recall curve (AUPR). By plotting the AUPR against the number of samples, we show that the trade-off has a, roughly speaking, sigmoid shape. An optimal number of samples corresponds to values on the ridge of the sigmoid.
Research center :
Luxembourg Centre for Systems Biomedicine (LCSB)
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Markdahl, Johan ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Colombo, Nicolo ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Thunberg, Johan ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Goncalves, Jorge ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
External co-authors :
yes
Language :
English
Title :
Experimental design trade-offs for gene regulatory network inference: an in silico study of the yeast Saccharomyces cerevisiae cell cycle
Publication date :
December 2017
Event name :
56th IEEE Conference on Decision and Control
Event place :
Melbourne, Australia
Event date :
from 12-12-2017 to 15-12-2017
Audience :
International
Main work title :
Proceedings of the 56th IEEE Conference on Decision and Control
Peer reviewed :
Peer reviewed
Focus Area :
Systems Biomedicine
Available on ORBilu :
since 04 January 2018

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