Big Data Analytics in Genomics (eBook)

Ka-Chun Wong is Assistant Professor in the Department of Computer Science at City University of Hong Kong. He received his B.Eng. in Computer Engineering in 2008 and his M.Phil. degree in the Department of Computer Science and Engineering in 2010, both from United College, the Chinese University of Hong Kong. He finished his PhD at the Department of Computer Science at University of Toronto . His research interests include computational biology, bioinformatics, evolutionary computation, big data analytics, application machine learning, and interdisciplinary research.

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.