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Discriminative pattern discovery on ...

Fassetti, Fabio.

Discriminative pattern discovery on biological networks

Record Type:	Electronic resources : Monograph/item
Title/Author:	Discriminative pattern discovery on biological networksby Fabio Fassetti, Simona E. Rombo, Cristina Serrao.
Author:	Fassetti, Fabio.
other author:	Rombo, Simona E.
Published:	Cham :Springer International Publishing :2017.
Description:	x, 45 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Biological systemsSimulation methods.
Online resource:	http://dx.doi.org/10.1007/978-3-319-63477-7
ISBN:	9783319634777$q(electronic bk.)

Discriminative pattern discovery on biological networks
Fassetti, Fabio.

Discriminative pattern discovery on biological networks[electronic resource] /by Fabio Fassetti, Simona E. Rombo, Cristina Serrao. - Cham :Springer International Publishing :2017. - x, 45 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..

Part I: Biological Networks -- Data Sources and Models -- Problems and Techniques -- Part II: Pattern Mining -- Exceptional Pattern Discovery -- Discriminating Graph Pattern Mining from Gene Expression Data.

This work provides a review of biological networks as a model for analysis, presenting and discussing a number of illuminating analyses. Biological networks are an effective model for providing insights about biological mechanisms. Networks with different characteristics are employed for representing different scenarios. This powerful model allows analysts to perform many kinds of analyses which can be mined to provide interesting information about underlying biological behaviors. The text also covers techniques for discovering exceptional patterns, such as a pattern accounting for local similarities and also collaborative effects involving interactions between multiple actors (for example genes) Among these exceptional patterns, of particular interest are discriminative patterns, namely those which are able to discriminate between two input populations (for example healthy/unhealthy samples) In addition, the work includes a discussion on the most recent proposal on discovering discriminative patterns, in which there is a labeled network for each sample, resulting in a database of networks representing a sample set. This enables the analyst to achieve a much finer analysis than with traditional techniques, which are only able to consider an aggregated network of each population.

ISBN: 9783319634777$q(electronic bk.)

Standard No.: 10.1007/978-3-319-63477-7doiSubjects--Topical Terms:

194057
Biological systems
--Simulation methods.

LC Class. No.: QH324.2

Dewey Class. No.: 570.113

Discriminative pattern discovery on biological networks
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