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Full Description
This handbook serves as an authoritative guide to Big Data pursuits in various branches of life sciences, with an emphasis on computational paradigms, tools, and techniques that are beginning to shape the Big Data advances within the life sciences domain. The term "life sciences" is meant to encompass a breadth of topics emerging from plant and animal sciences, human health and medicine, and microbiology.
Contents
Overviewto 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.
