Mining Omics Data: From Correlation to Independence - Couverture souple

Müller, Nikola

 
9783838135052: Mining Omics Data: From Correlation to Independence
Couverture souple
ISBN 10 : 3838135059 ISBN 13 : 9783838135052
Editeur : Südwestdeutscher Verlag für Hochschulschriften, 2013

Synopsis

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.

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Présentation de l'éditeur

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.

Biographie de l'auteur

Nikola Müller studied Bioinformatics in Munich, Germany, and performed her doctoral work in bioinformatics at the Max Planck Institute of Biochemistry. She received her PhD at the Institute for Informatics at the Ludwig-Maximilians-University Munich.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Südwestdeutscher Verlag für Hochschulschriften
Date d'édition
2013
Langue
anglais
ISBN 10 
3838135059
ISBN 13 
9783838135052
Reliure
Broché
Nombre de pages
220
Coordonnées du fabricant
non disponible
Personne responsable
non disponible