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Biomedical subjects

John G Olyarchuk

Publications and source records attributed to John G Olyarchuk.

2 recordsLinked to original sources

SynDB: a Synapse protein DataBase based on synapse ontology.

A synapse is the junction across which a nerve impulse passes from an axon terminal to a neuron, muscle cell or gland cell. The functions and building molecules of the synapse are essential to almost all neurobiological processes. To describe synaptic structures and functions, we have developed Synapse Ontology (SynO), a hierarchical representation that includes 177 terms with hundreds of synonyms and branches up to eight levels deep. associated 125 additional protein keywords and 109 InterPro domains with these SynO terms. Using a combination of automated keyword searches, domain searches and manual curation, we collected 14,000 non-redundant synapse-related proteins, including 3000 in human. We extensively annotated the proteins with information about sequence, structure, function, expression, pathways, interactions and disease associations and with hyperlinks to external databases. The data are stored and presented in the Synapse protein DataBase (SynDB, http://syndb.cbi.pku.edu.cn). SynDB can be interactively browsed by SynO, Gene Ontology (GO), domain families, species, chromosomal locations or Tribe-MCL clusters. It can also be searched by text (including Boolean operators) or by sequence similarity. SynDB is the most comprehensive database to date for synaptic proteins.

Animals↗

Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary.

MOTIVATION: High-throughput technologies such as DNA sequencing and microarrays have created the need for automated annotation of large sets of genes, including whole genomes, and automated identification of pathways. Ontologies, such as the popular Gene Ontology (GO), provide a common controlled vocabulary for these types of automated analysis. Yet, while GO offers tremendous value, it also has certain limitations such as the lack of direct association with pathways. RESULTS: We demonstrated the use of the KEGG Orthology (KO), part of the KEGG suite of resources, as an alternative controlled vocabulary for automated annotation and pathway identification. We developed a KO-Based Annotation System (KOBAS) that can automatically annotate a set of sequences with KO terms and identify both the most frequent and the statistically significantly enriched pathways. Results from both whole genome and microarray gene cluster annotations with KOBAS are comparable and complementary to known annotations. KOBAS is a freely available stand-alone Python program that can contribute significantly to genome annotation and microarray analysis.

Artificial Intelligence↗