Big Data in Omics and Imaging, Two Volume Set
  • Leveringstid 5-8 hverdage
  • Forventet levering 02-12-2019
Format:
Bog, hardback
Udgivelsesdato:
22-01-2016
Sprog:
Engelsk
  • Beskrivelse
  • Yderligere info
  • Anmeldelser

FEATURESBridges the gap between the traditional statistical methods and computational tools for small genetic and epigenetic data analysis and the modern advanced statistical methods for big dataProvides tools for high dimensional data reductionDiscusses searching algorithms for model and variable selection including randomization algorithms, Proximal methods and matrix subset selectionProvides real-world examples and case studiesWill have an accompanying website with R codeProvides a natural extension and companion volume to Big Data in Omic and Imaging: Association Analysis, but can be read independently. Introduce causal inference theory to genomic, epigenomic and imaging data analysis Develop novel statistics for genome-wide causation studies and epigenome-wide causation studies. Bridge the gap between the traditional association analysis and modern causation analysis Use combinatorial optimization methods and various causal models as a general framework for inferring multilevel omic and image causal networks Present statistical methods and computational algorithms for searching causal paths from genetic variant to disease Develop causal machine learning methods integrating causal inference and machine learning Develop statistics for testing significant difference in directed edge, path, and graphs, and for assessing causal relationships between two networks The book is designed for graduate students and researchers in genomics, bioinformatics, and data science. It represents the paradigm shift of genetic studies of complex diseases- from shallow to deep genomic analysis, from low-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from homogeneous populations to heterogeneous population and pedigree data analysis. Topics covered are: advanced matrix theory, convex optimization algorithms, generalized low rank models, functional data analysis techniques, deep learning principle and machine learning methods for modern association, interaction, pathway and network analysis of rare and common variants, biomarker identification, disease risk and drug response prediction.

Vis mereVis mindre

Udgivelsesdato:
22-01-2016
ISBN13:
9780367002183
Format:
Hardback
  • Forfattere

  • Bibliotekernes beskrivelse

    Contains 2 Hardbacks

Vis mereVis mindre

Vis mereVis mindre

Fandt du ikke hvad du søgte?

Hvis denne bog ikke er noget for dig, kan du benytte kategorierne nedenfor til at finde andre titler. Klik på en kategori for at se lignende bøger.

Velkommen til Saxo - din danske boghandel!

Hos os kan du handle som Gæst, Saxo-bruger eller Saxo Premium-medlem. Du bestemmer selv, og vores kundeservice sidder altid klar med hjælp.

Om medlemspriser hos Saxo

Hvis du køber til medlemspris, bliver du automatisk medlem og får del i de mange fede fordele. De første 30 dage er gratis for nye brugere, og derefter koster det kun 99,-/md. Medlemskabet fornyes automatisk, og du kan altid opsige det. Læs mere om fordelene ved Saxo Premium her.