Big Data Analytics in Genomics

This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at a...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Wong, Ka-Chun (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Temas:
Bioinformatics.
Data mining.
Biometry.
Population genetics.
Computational and Systems Biology.
Data Mining and Knowledge Discovery.
Biostatistics.
Population Genetics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction to Statistical Methods for Integrative Analysis of Genomic Data
  • Robust Methods for Expression Quantitative Trait Loci Mapping
  • Causal Inference and Structure Learning of Genotype-Phenotype Networks using Genetic Variation
  • Genomic Applications of the Neyman-Pearson Classification Paradigm
  • Improving Re-annotation of Annotated Eukaryotic Genomes
  • State-of-the-art in Smith-Waterman Protein Database Search
  • A Survey of Computational Methods for Protein Function Prediction
  • Genome Wide Mapping of Nucleosome Position and Histone Code Polymorphisms in Yeast
  • Perspectives of Machine Learning Techniques in Big Data Mining of Cancer
  • Mining Massive Genomic Data for Therapeutic Biomarker Discovery in Cancer: Resources, Tools, and Algorithms
  • NGC Analysis of Somatic Mutations in Cancer Genomes
  • OncoMiner: A Pipeline for Bioinformatics Analysis of Exonic Sequence Variants in Cancer
  • A Bioinformatics Approach for Understanding Genotype-Phenotype Correlation in Breast Cancer.

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