Abstract
Network inference in a living cell is one of the main themes in high-throughput assays, and some computational methods have been developed to deduce the relationships between the genes and proteins. Recently, we developed a method for inferring a network from a large amount of numerical data obtained from high-throughput analyses. Our method is now open to the public on the web, named as ASIAN (http://eureka.cbrc.jp/asian/).
In this chapter, we describe the ASIAN (Automatic System for Inferring A Network) web server for inferring a network from a large amount of numerical data, based on graphical Gaussian modeling (GGM) in combination with hierarchical clustering. GGM is based on a simple mathematical structure, which is the calculation of the inverse of the correlation coefficient matrix between variables. The ASIAN web server can analyze a wide variety of data within a reasonable computational time. The server allows users to input the numerical data, and it outputs the dendrogram of the objects by several hierarchical clustering techniques, the cluster number is estimated by a stopping rule for hierarchical clustering, and the network between the clusters by GGM, with the respective graphical presentations. ASIAN is useful for inferring the framework of networks from redundant empirical data, in addition to the clustering, concomitant with the estimation of the cluster number. In particular, the visual presentation of the result provides an intuitive means for understanding the putative network between the objects.
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© 2009 Humana Press, a part of Springer Science+Business Media, LLC
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Aburatani, S., Saito, S., Horimoto, K. (2009). ASIAN: Network Inference Web Server. In: Krawetz, S. (eds) Bioinformatics for Systems Biology. Humana Press. https://doi.org/10.1007/978-1-59745-440-7_29
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DOI: https://doi.org/10.1007/978-1-59745-440-7_29
Publisher Name: Humana Press
Print ISBN: 978-1-934115-02-2
Online ISBN: 978-1-59745-440-7
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