Titlebook: Gene Regulatory Networks; Methods and Protocol Guido Sanguinetti,Van Anh Huynh-Thu Book 2019 Springer Science+Business Media, LLC, part of

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Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks froactical applications with pointers to publicly available software implementations are included. The chapter concludes with a comprehensive comparative benchmark study on simulated data and a real-work application taken from the current plant systems biology.

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發(fā)怨言

,Aus der forstlichen Ger?thekammer,ide an introduction to the basic concepts underpinning network inference tools, attempting a categorization which highlights commonalities and relative strengths. While the chapter is meant to be self-contained, the material presented should provide a useful background to the later, more specialized chapters of this book.

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Gene Regulatory Network Inference: An Introductory Survey,ide an introduction to the basic concepts underpinning network inference tools, attempting a categorization which highlights commonalities and relative strengths. While the chapter is meant to be self-contained, the material presented should provide a useful background to the later, more specialized chapters of this book.

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Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Stlogical networks, when the data is observational. We also discuss its ability to decipher the causal information flow as observed in gene expression. We also illustrate our exploration by experiments on small simulated networks as well as on a real biological data set.

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Gene Regulatory Network Inference: An Introductory Survey,he late 1990s, reconstructing the structure of such networks has been a central computational problem in systems biology. While the problem is certainly not solved in its entirety, considerable progress has been made in the last two decades, with mature tools now available. This chapter aims to prov