Genomic annotations are the focal point of sequencing, bioinformatics analysis, and molecular biology. They are the means by which we attach what we know about a genome to its sequence. Unfortunately, biological terminology is notoriously ambiguous; the same word is often used to describe more than one thing and there are many dialects. For example, does a coding sequence (CDS) contain the stop codon or is the stop codon part of the 3'-untranslated region (3' UTR)? There really is no right or wrong answer to such questions, but consistency is crucial when attempting to compare annotations from different sources, or even when comparing annotations performed by the same group over an extended period of time.
Regroups a set of terms and relationships used to describe the features and attributes of biological sequence. SO includes different kinds of features which can be located on the sequence. It maintains and updates the specification and provides the underlying ontological structure. The terminology was used to annotate the human reference genome with a set of variants from both COSMIC and dbSNP.
Provides the means to describe computationally inferred genome annotations of biological objects typically found in a genome sequence annotation data file. GBOL is modular in design, extendible and linked to existing ontologies. Additionally, it can describe the linked data provenance of the extraction process of genetic information from genome sequences. GBOL is available under ontology and API format.
Provides the collective landscapes of multiple targets, activity profiles, gene ontologies, biological pathways and diseases for the classes of medicinal, food, edible, agricultural and garden plants. CMAUP is a resource that offers multiple search modes including keywords, plant usage classes, species families, targets, KEGG pathways, gene ontologies, diseases (ICD code) and geographical locations.
Automatically augments annotations in Gene Ontology annotations (GOA) with additional context. PhenoGO is a multi-organism database that integrates existing Gene Ontology annotations with phenotypic context using a number of widely used structured ontologies. It was developed to facilitate high throughput mining of experimental, phenotypic or disease contexts associated to gene-to-GO annotations.
Provides a repository of profiles diseases and genes associated with related drugs, biological phenomena and anatomy described with MeSH vocabulary. Gendoo includes more than 1700000 associations. The database allows users to visualize associations between OMIM entries and relevant MeSH terms and compare different features. Searches can be made by OMIM IDs, OMIM titles, Entrez Gene IDs, gene names or MeSH terms.
Provides four orthogonal ontologies. eVOC aims to provide an appropriately detailed set of terms for describing the sample source of cDNA and SAGE libraries and labeled target cDNAs for microarray experiments. It can be used to identify not only tissue-specific spliceforms, but also splicing that is specific to certain developmental stages, cell types, and pathological states, or any combination of these states.
Provides structured knowledge about the cellular components, processes, and functions encoded by genes. NeXO is a data-driven gene ontology (GO) inferred directly from omics data. It uses a principled computational approach which integrates evidence from hundreds of thousands of individual gene and protein interactions to construct a complete hierarchy of cellular components and processes. This data-derived ontology aligns with known biological machinery in the GO Database and also uncovers many new structures.