Biomedical subjects

Gordon Shepherd

Publications and source records attributed to Gordon Shepherd.

4 recordsLinked to original sources

PubMed2005

Performance evaluation of a thermal Doppler Michelson interferometer system.

The thermal Doppler Michelson interferometer is the primary element of a proposed limb-viewing satellite instrument called SWIFT (Stratospheric Wind Interferometer for Transport studies). SWIFT is intended to measure stratospheric wind velocities in the altitude range of 15-45 km. SWIFT also uses narrowband tandem etalon filters made of germanium to select a line out of the thermal spectrum. The instrument uses the same technique of phase-stepping interferometry employed by the Wind Imaging Interferometer onboard the Upper Atmosphere Research Satellite. A thermal emission line of ozone near 9 microm is used to detect the Doppler shift due to winds. A test bed was set up for this instrument that included the Michelson interferometer and the etalon filters. For the test bed work, we investigate the behavior of individual components and their combination and report the results.

Journal Article↗

PubMed2004

QIS: A framework for biomedical database federation.

Query Integrator System (QIS) is a database mediator framework intended to address robust data integration from continuously changing heterogeneous data sources in the biosciences. Currently in the advanced prototype stage, it is being used on a production basis to integrate data from neuroscience databases developed for the SenseLab project at Yale University with external neuroscience and genomics databases. The QIS framework uses standard technologies and is intended to be deployable by administrators with a moderate level of technological expertise: It comes with various tools, such as interfaces for the design of distributed queries. The QIS architecture is based on a set of distributed network-based servers, data source servers, integration servers, and ontology servers, that exchange metadata as well as mappings of both metadata and data elements to elements in an ontology. Metadata version difference determination coupled with decomposition of stored queries is used as the basis for partial query recovery when the schema of data sources alters.

Computer Communication Networks↗

PubMed2003

Achieving evolvable Web-database bioscience applications using the EAV/CR framework: recent advances.

The EAV/CR framework, designed for database support of rapidly evolving scientific domains, utilizes metadata to facilitate schema maintenance and automatic generation of Web-enabled browsing interfaces to the data. EAV/CR is used in SenseLab, a neuroscience database that is part of the national Human Brain Project. This report describes various enhancements to the framework. These include (1) the ability to create "portals" that present different subsets of the schema to users with a particular research focus, (2) a generic XML-based protocol to assist data extraction and population of the database by external agents, (3) a limited form of ad hoc data query, and (4) semantic descriptors for interclass relationships and links to controlled vocabularies such as the UMLS.

Database Management Systems↗

PubMed2002

Olfactory Receptor Database: a metadata-driven automated population from sources of gene and protein sequences.

The Olfactory Receptor Database (ORDB; http://senselab.med.yale.edu/senselab/ordb) is a central repository of olfactory receptor (OR) and olfactory receptor-like gene and protein sequences. To deal with the very large OR gene family, we have constructed an algorithm that automatically downloads sequences from web sources such as GenBank and SWISS-PROT into the database. The algorithm uses hypertext markup language (HTML) parsing techniques that extract information relevant to ORDB. The information is then correlated with the metadata in the ORDB knowledge base to encode the unstructured text extracted into the structured format compliant with the database architecture, entity attribute value with classes and relationship (EAV/CR), which supports the SenseLab project as a whole. Three population methods: batch, automatic and semi-automatic population are discussed. The data is imported into the database using extensible markup language (XML).

Algorithms↗