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Juanjo Vega

dblp:73/7390 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › data integration
biological data integration
0.222012
Integrating human and murine anatomical gene expression data for improved comparisons · Bioinform. 2012
aGEM: an integrative system for analyzing spatial-temporal gene-expression information · Bioinform. 2009
Bioinformatics and computational biology › biological database
gene expression database
0.222012
Integrating human and murine anatomical gene expression data for improved comparisons · Bioinform. 2012
aGEM: an integrative system for analyzing spatial-temporal gene-expression information · Bioinform. 2009
Bioinformatics and computational biology › data integration › biological data integration
distributed annotation system
0.112009
aGEM: an integrative system for analyzing spatial-temporal gene-expression information · Bioinform. 2009

Methods — techniques the papers use, named apart from their topics

correlation analysis · 0.1distributed annotation system protocol · 0.1
YearPublicationVenuePosition
2012 Integrating human and murine anatomical gene expression data for improved comparisons
abstract
MOTIVATION: Information concerning the gene expression pattern in four dimensions (species, genes, anatomy and developmental stage) is crucial for unraveling the roles of genes through time. There are a variety of anatomical gene expression databases, but extracting information from them can be hampered by their diversity and heterogeneity. RESULTS: aGEM 3.1 (anatomic Gene Expression Mapping) addresses the issues of diversity and heterogeneity of anatomical gene expression databases by integrating six mouse gene expression resources (EMAGE, GXD, GENSAT, Allen Brain Atlas data base, EUREXPRESS and BioGPS) and three human gene expression databases (HUDSEN, Human Protein Atlas and BioGPS). Furthermore, aGEM 3.1 provides new cross analysis tools to bridge these resources. AVAILABILITY AND IMPLEMENTATION: aGEM 3.1 can be queried using gene and anatomical structure. Output information is presented in a friendly format, allowing the user to display expression maps and correlation matrices for a gene or structure during development. An in-depth study of a specific developmental stage is also possible using heatmaps that relate gene expression with anatomical components. http://agem.cnb.csic.es CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Natalia Jiménez-Lozano, Joan Segura, José Ramón Macías, Juanjo Vega, José María Carazo
Bioinform.4
2009 aGEM: an integrative system for analyzing spatial-temporal gene-expression information
abstract
Abstract Motivation: The work presented here describes the ‘anatomical Gene-Expression Mapping (aGEM)’ Platform, a development conceived to integrate phenotypic information with the spatial and temporal distributions of genes expressed in the mouse. The aGEM Platform has been built by extending the Distributed Annotation System (DAS) protocol, which was originally designed to share genome annotations over the WWW. DAS is a client-server system in which a single client integrates information from multiple distributed servers. Results: The aGEM Platform provides information to answer three main questions. (i) Which genes are expressed in a given mouse anatomical component? (ii) In which mouse anatomical structures are a given gene or set of genes expressed? And (iii) is there any correlation among these findings? Currently, this Platform includes several well-known mouse resources (EMAGE, GXD and GENSAT), hosting gene-expression data mostly obtained from in situ techniques together with a broad set of image-derived annotations. Availability: The Platform is optimized for Firefox 3.0 and it is accessed through a friendly and intuitive display: http://agem.cnb.csic.es Contact: [email protected] Supplementary information: Supplementary data are available at http://bioweb.cnb.csic.es/VisualOmics/aGEM/home.html and http://bioweb.cnb.csic.es/VisualOmics/index_VO.html and Bioinformatics online.
Natalia Jiménez-Lozano, Joan Segura, José Ramón Macías, Juanjo Vega, José María Carazo
Bioinform.4