The human microbiome has emerged as a hitherto unknown causal factor in a number of disease, ranging from cancer, cardiovascular disease, and obesity. To understand the biochemical mechanisms of the human microbiome in these diseases, researchers must be able to store biochemical pathway, transcriptomic, and metabolomic datasets in a coherent and compatible form. We propose to construct a cloud-based microbiome analytics platform service that provides both common data processing tools, along with integration of a standards-compliant database that can be queried to provide cross-dataset and inter-modal data comparative analytics.
Public Health Relevance Statement: The human microbiome is the collection of bacteria that live inside of all people, and researchers have determined that these bacteria play a causal role in many diseases such as obesity. Our proposal will create an analysis system for processing large volumes of data from the human microbiome, allowing efficient and easy data processing for both academic researchers and for-profit biotechnology companies.
Project Terms: Bacteria; base; Big Data; Biochemical; Biochemical Pathway; Bioinformatics; Biotechnology; Businesses; Cardiovascular Diseases; clinical phenotype; cloud based; Cloud Computing; Cloud Service; Collection; commercialization; comparative; Computer software; computerized data processing; Data; data access; Data Analyses; Data Analytics; data integration; Data Set; Databases; design; Development; Disease; Eating; Goals; Government; Human Microbiome; improved; innovation; International; Intestines; Licensing; Life; Link; Malignant Neoplasms; mental state; Metabolic Pathway; Metabolism; metabolomics; metagenomic sequencing; Metagenomics; Methods; microbial; microbiome; Modality; Molecular Profiling; next generation sequencing; novel; Obesity; open source; Pathway interactions; pathway tools; Phase; Play; prediction algorithm; Private Sector; Process; prototype; Publishing; Reading; Reporting; Research Personnel; Role; Running; Sampling; Services; software as a service; System; Systems Analysis; Testing; Therapeutic Intervention; Time; tool; transcriptomics; type I and type II diabetes; Validation; web services
