Mining Omics Data : From Correlation to Independence

Language: English

Published by Südwestdeutscher Verlag Für Hochschulschriften, 2013

3838135059 / 9783838135052

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Biological studies across all omics fields generate vast amounts of data. To understand these complex data, biologically motivated data mining techniques are indispensable. In this dissertation, biological problems were individually addressed by using solutions from computational sciences. The interactome study identified graph clusters: A parameter-free graph-clustering algorithm was developed using graph compression to find highly interlinked proteins sharing similar characteristics. The lipidome study analyzed co-regulations: To reveal those lipids similarly responding to biological factors, a differential Gaussian Graphical Model was introduced accounting for disease-specificity. The cytome study of single cells aimed at understanding cellular systems: A novel noise robust source separation technique reliably extracted independent components from images describing protein behaviors. The study of peptides required the detection outstanding observations: By assessing regularities, an outlier detection algorithm was based on compression efficacy of independent components. All algorithms fulfilled diverse constraints, but were met with standard correlation and dependency methods.…

Seller Inventory # 9783838135052

Title
Mining Omics Data : From Correlation to Independence
Author
Nikola Müller
Publisher
Südwestdeutscher Verlag Für Hochschulschriften
Publication year
2013
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3838135059
ISBN 13
9783838135052
Item weight
346 grams
Dimensions
220x150x14 mm

AHA-BUCH GmbH

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