The rapid growth in biological sequence data is revolutionizing our understanding of genotypic diversity and challenging conventional approaches to informatics. Due to increasing availability of genomic data, traditional bioinformatic tools require substantial computational time and creation of ever larger indices each time a researcher seeks to gain insight from the data. To address these challenges, we pre-compute important relationships between biological entities and capture this information in a relational database. The database can be queried across  millions of entities and returns results in a fraction of the time required by traditional methods. In this paper, we describeOMXWare  , a comprehensive database relating genotype to phenotype for bacterial life. Continually updated, OMXWare 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 GeneOntology , KEGG, MetaCyc, and Reactome. OMXWare maps 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 relationships within OMXWare . We describe the data selection, the pipeline to create and update OMXWare, and developer tools (Python SDK and Rest APIs) which allow researchers to efficiently study 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 describeIBM Functional Genomics Platform (formerly known as OMXWare) , a comprehensive database relating genotype to phenotype for bacterial life. Continually updated, IBM 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. IBM 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 IBM Functional Genomics Platform, and the developer tools (Python SDK and REST APIs) which allow researchers to efficiently study microbial life at scale.
R
Due to
With the
R
creation of ever larger
the creation of ever-larger
R
pre-compute
pre-computed
R
and capture
spanning the Central Dogma of Molecular Biology and captured
A
hundreds of
R
describeOMXWare
describe
A
IBM Functional Genomics Platform
A
(formerly known as OMXWare)
R
OMXWare
IBM Functional Genomics Platform
R
GeneOntology
Gene Ontology
R
OMXWare maps
IBM Functional Genomics Platform maps all of the many-to-many
R
relationships within OMXWare
connections
R
OMXWare, and
the IBM Functional Genomics Platform, and the
R
Rest
REST