Demo Data from EDBT 2026 / reviewers in the wild / expert
José Ramón Macías
dblp:76/7390
· DBLP profile ↗
3ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0003-2621-6806ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 1 first-author · 1 since 2021
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
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
structural bioinformatics |
0.5 | 1 | 2021 | 3DBionotes COVID-19 edition · Bioinform. 2021 |
Bioinformatics and computational biology › data integration
biological data integration |
0.2 | 2 | 2012 | 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 |
0.2 | 2 | 2012 | 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 › microbiology
virology |
0.1 | 1 | 2021 | 3DBionotes COVID-19 edition · Bioinform. 2021 |
Bioinformatics and computational biology › data integration › biological data integration
distributed annotation system |
0.1 | 1 | 2009 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | 3DBionotes COVID-19 editionabstractSUMMARY: The web platform 3DBionotes-WS integrates multiple web services and an interactive web viewer to provide a unified environment in which biological annotations can be analyzed in their structural context. Since the COVID-19 outbreak, new structural data from many viral proteins have been provided at a very fast pace. This effort includes many cryogenic electron microscopy (cryo-EM) studies, together with more traditional ones (X-rays, NMR), using several modeling approaches and complemented with structural predictions. At the same time, a plethora of new genomics and interactomics information (including fragment screening and structure-based virtual screening efforts) have been made available from different servers. In this context, we have developed 3DBionotes-COVID-19 as an answer to: (i) the need to explore multiomics data in a unified context with a special focus on structural information and (ii) the drive to incorporate quality measurements, especially in the form of advanced validation metrics for cryo-EM. AVAILABILITY AND IMPLEMENTATION: https://3dbionotes.cnb.csic.es/ws/covid19. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. José Ramón Macías, Rubén Sánchez García, Pablo Conesa, Erney Ramírez-Aportela, Marta Martínez, Carlos Wert-Carvajal, Alberto M. Parra-Perez, Joan Segura Mora, Sam Horrell, Andrea Thorn, Carlos Oscar Sánchez Sorzano, José María Carazo |
Bioinform. | 1 |
| 2012 | Integrating human and murine anatomical gene expression data for improved comparisonsabstractMOTIVATION: 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. | 3 |
| 2009 | aGEM: an integrative system for analyzing spatial-temporal gene-expression informationabstractAbstract 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. | 3 |