Name
Title | ||
|---|---|---|
Experimental design trade-offs for gene regulatory network inference: An in silico study of the yeast Saccharomyces cerevisiae cell cycle |
Abstract | ||
|---|---|---|
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 G
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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 tradeoff has a, roughly speaking, sigmoid shape. An optimal number of samples corresponds to values on the ridge of the sigmoid. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CDC.2017.8263701 | 2017 IEEE 56th Annual Conference on Decision and Control (CDC) |
Keywords | Field | DocType |
experimental design trade-offs,gene regulatory network inference,time-series,high throughput gene,cell systems,GRN inference,Markovian jump process model,Saccharomyces cerevisiae cell cycle,linear regression model,in silico study,network topology,GRN model,LASSO method,metabolites,precision-recall curve,sigmoid ridge,proteins | Inference,Lasso (statistics),Network topology,Artificial intelligence,Saccharomyces cerevisiae,Computational biology,Gene regulatory network,Machine learning,Mathematics,Linear regression,In silico,Sigmoid function | Conference |
ISSN | ISBN | Citations |
0743-1546 | 978-1-5090-2874-0 | 0 |
PageRank | References | Authors |
0.34 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| johan markdahl | 1 | 29 | 7.43 |
| Nicolò Colombo | 2 | 0 | 0.34 |
| Johan Thunberg | 3 | 138 | 19.15 |
| Goncalves, J. | 4 | 404 | 42.24 |