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Biomedical subjects

Luis Marenco

Publications and source records attributed to Luis Marenco.

7 recordsLinked to original sources
PubMed2006

Dynamic tables: an architecture for managing evolving, heterogeneous biomedical data in relational database management systems.

Data sparsity and schema evolution issues affecting clinical informatics and bioinformatics communities have led to the adoption of vertical or object-attribute-value-based database schemas to overcome limitations posed when using conventional relational database technology. This paper explores these issues and discusses why biomedical data are difficult to model using conventional relational techniques. The authors propose a solution to these obstacles based on a relational database engine using a sparse, column-store architecture. The authors provide benchmarks comparing the performance of queries and schema-modification operations using three different strategies: (1) the standard conventional relational design; (2) past approaches used by biomedical informatics researchers; and (3) their sparse, column-store architecture. The performance results show that their architecture is a promising technique for storing and processing many types of data that are not handled well by the other two semantic data models.

Computational Biology↗
PubMed2006

ResourceLog: an embeddable tool for dynamically monitoring the usage of web-based bioscience resources.

The present study described an open source application, ResourceLog, that allows website administrators to record and analyze the usage of online resources. The application includes four components: logging, data mining, administrative interface, and back-end database. The logging component is embedded in the host website. It extracts and streamlines information about the Web visitors, the scripts, and dynamic parameters from each page request. The data mining component runs as a set of scheduled tasks that identify visitors of interest, such as those who have heavily used the resources. The identified visitors will be automatically subjected to a voluntary user survey. The usage of the website content can be monitored through the administrative interface and subjected to statistical analyses. As a pilot project, ResourceLog has been implemented in SenseLab, a Web-based neuroscience database system. ResourceLog provides a robust and useful tool to aid system evaluation of a resource-driven Web application, with a focus on determining the effectiveness of data sharing in the field and with the general public.

Bibliometrics↗
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↗
PubMed2004

Informatics approaches to functional MRI odor mapping of the rodent olfactory bulb: OdorMapBuilder and OdorMapDB.

The present study applies informatics tools to aid and extend fMRI analysis of the coding mechanism of neural signals in the rodent olfactory system. Odor stimulation evokes unique spatial patterns of activity in the glomerular layer of the mammalian olfactory bulb (OB). An open-source software program, OdorMap-Builder, has been developed to process the high resolution anatomical and functional MRI images of the OB and to generate single two-dimensional flat maps, called odor maps, that describe the spatial activity patterns in the entire glomerular layer. Odor maps help identify the spatial activity patterns from the tremendous amount of fMRI data and they serve as ideal representation of space coding for the olfactory signals in the OB in response to a given odor stimulation. Based on the fMRI technology, OdorMapBuilder provides comparable odor maps on the intra-subject basis, a significant step towards the detailed analyses of the effects of odor types and/or concentrations. In addition, a new database, OdorMapDB, is developed to provide a repository for the generated odor maps. Web interfaces to the database are provided for the data entry, modification and retrieval. OdorMapDB is based on the EAV/CR (entity-attribute-value with classes and relationships) architecture and it is integrated with two other SenseLab olfactory databases: the olfactory receptor and odor databases. Both OdorMapBuilder and OdorMapDB should serve as useful tools and resources for the field and help facilitate experimental research in understanding the olfactory system and the mechanism for smell perception.

Animals↗
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↗