Mining Omics Data

Name: Mining Omics Data
Brand: Sudwestdeutscher Verlag Fur Hochschulschriften AG
SKU: 9783838135052
Price: 431.8 RON
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From Correlation to Independence

Autor: Nikola Müller

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Editura: Sudwestdeutscher Verlag Fur Hochschulschriften AG

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Biological studies across all omics fields generate vast amounts of data. To understand these comple...

Informații despre carte

Autor

Nikola Müller

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2013

Pagini

220

EAN

9783838135052

ISBN

3838135059

Enbook ID

06958183

Editura

Sudwestdeutscher Verlag Fur Hochschulschriften AG

Greutate

327

Dimensiuni

152 x 229 x 13

Descriere completă

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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Mining Omics Data

From Correlation to Independence

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