Functional Genomics Platform, A Cloud-Based Platform for Studying Microbial Life at Scale.

The rapid growth in biological sequence data is revolutionizing our understanding of genotypic diversity and challenging conventional approaches to informatics. With the increasing availability of genomic data, traditional bioinformatic tools require substantial computational time and the creation of ever-larger indices each time a researcher seeks to gain insight from the data. To address these challenges, we pre-computed important relationships between biological entities spanning the Central Dogma of Molecular Biology and captured this information in a relational database. The database can be queried across hundreds of millions of entities and returns results in a fraction of the time required by traditional methods. In this paper, we describe Functional Genomics Platform (formerly known as OMXWare), a comprehensive database relating genotype to phenotype for bacterial life. Continually updated, the Functional Genomics Platform today contains data derived from 200,000 curated, self-consistently assembled genomes. The database stores functional data for over 68 million genes, 52 million proteins, and 239 million domains with associated biological activity annotations from Gene Ontology, KEGG, MetaCyc, and Reactome. The Functional Genomics Platform maps all of the many-to-many connections between each biological entity including the originating genome, gene, protein, and protein domain. Various microbial studies, from infectious disease to environmental health, can benefit from the rich data and connections. We describe the data selection, the pipeline to create and update the Functional Genomics Platform, and the developer tools (Python SDK and REST APIs)which allow researchers to efficiently study microbial life at scale.

From data to insight: work practices of analysts in the enterprise.

With greater availability of data, businesses are increasingly becoming data-driven enterprises, establishing standards for data acquisition, processing, infrastructure, and decision making. Enterprises now have people dedicated to performing analytic work to support decision makers. To better understand analytic work, particularly the role of enterprise business analysts, researchers interviewed 34 analysts at a large corporation. Analytical work occurred in an ecosystem of data, tools, and people; the ecosystem's overall quality and efficiency depended on the amount of coordination and collaboration. Analysts were the bridge between business and IT, closing the semantic gap between datasets, tools, and people. This article provides an overview of the analytic work in the enterprise, describing challenges in data, tools, and practices and identifying opportunities for new tools for collaborative analytics.