Handbook of Big Data Analytics in Life Sciences (Hardcover)

Overview: Big Data challenges, current state of the art, and a roadmap to the future. Core Algorithms and Techniques. Genome assembly. Read mapping and other NGS techniques. Proteomics. Metagenomic taxonomic classification and assembly. Metagenomics functional annotation. RNAseq algorithms. Protein networks. Systems biology and network analysis. Networks construction. Network science and epidemiology. BD Advances in Plant Sciences. iPlant collaborative. Plant databases. Phenomics. BD Advances in Medicine and Clinical Sciences. Advances in cancer biology. Clinical and translational research. Pubmed. ENCODE architecture. Brain initiative. HealthMap project. Integrative approaches to medical diagnostic. BD Advances in Environmental Microbiology. DOE Kbase. Metaproteomics. Big Data Management. NCBI. JGI. EMBO. BGI. Million cancer genome warehouse. Aggregation of large genomics data and computations. Cyberinfrastructure for Big Data in Life Sciences. Galaxy. BioKepler. SeqAn/OpenMS. DOE KBase. AWS/EC2. Scientific workflows in epidemiology. Computational federations.