Big Data Analytics in Genomics
-15%
portes grátis
Big Data Analytics in Genomics
Wong, Ka-Chun
Springer International Publishing AG
04/2018
428
Mole
Inglês
9783319823126
15 a 20 dias
6555
Descrição não disponível.
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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Big Data;Genomics;Data Mining;Genome Research;Biostatistics;Molecular Genetics;Data Analytics;Biology;Bioinformatics;Computational Biology;Cancer Research;Cancer Genomes;Computational Science;Scientific Computing;Computational Annotation
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
