Bioinformatic analysis was carried out to categorize proteins based on biological processes, cellular component and molecular function classification using annotations in Human Protein Reference Database (HPRD, http://hprd.org) [ 35], which is in compliance with gene ontology (GO) standards.
Bioinformatics analysis was carried out to categorize proteins based on biological processes, cellular component and molecular function using annotations in Human Protein Reference Database (HPRD) [ 15, 16], which is in compliance with gene ontology (GO) standards.
Enrichment analysis of GO terms was performed to examine the functional distribution of the 94 differentially expressed proteins using annotations in Human Protein Reference Database (HPRD, http://www.hprd.org) [ 23], which follows gene ontology (GO) standards.
Bioinformatics analysis was carried out to categorize proteins based on biological processes, cellular component, and molecular function classification using annotations in Human Protein Reference Database (HPRD, http://hprd.org/) [ 18], which is in compliance with gene ontology (GO) standards.
Supported ontologies and standards include MIRIAM, the Systems Biology Ontology (SBO; Le Novère, 2006) and Gene Ontology (GO; Ashburner et al., 2000).
This article describes the necessity of developing robotics ontologies and standards focusing on the past and current research efforts.
Accordingly, the talks given during the session on Ontologies and Standards either highlighted select go-to resources, or lent transparency to widely used procedures.
Samadian et al. (University of British Columbia, Canada) utilized existing ontologies and standards for scientific data representation to build a Semantic Web Service-based approach to automatic measurement-unit harmonization [ 13].
They have exposed the associated data sources through SPARQL query endpoints, and have also agreed on a concise set of ontologies and standards for exchanging experimental data and biomedical information (17).
This conference addresses many aspects of biocuration including: community annotation; protein annotation; functional annotation; pathways; structure; complexes; interactions; genomics; metagenomics; comparative genomics; biocuration workflows, productivity and analysis tools; the integration of text mining in biocuration workflows; and ontologies and standards.
Mi and Thomas also argue that in order to succeed, ontologies and standards in bioscience should be designed not only to be readable by computers, but also to be accurate and intuitive to (human) biologists [ 38].
