Programación en Java de un entorno de control para un sistema domótico

El resultado de este Proyecto de Fin de Carrera, la aplicación de control domótico para la infraestructura del sistema domótico de Ergodomus S.L, ha satisfecho las expectativas de la empresa, cumpliendo con los requisitos indispensables solicitados por ésta además de algunos otros en principio no imprescindibles. La aplicación ha ido más allá del mismo control del sistema domótico, ya que posibilidades como almacenar un backup en archivos xml la configuración de una infraestructura dada permite su replicación tantas veces como sea necesaria con un coste mínimo, independizando los módulos de E/S físicos, de la programación que guardan. Además, esto también facilita enormemente la modificación de esta programación y su análisis por el personal de la empresa. El aspecto que ha requerido un mayor esfuerzo ha sido la especificación de requisitos y su equivalencia en cuanto a código, ya que a lo largo de todo el desarrollo del sistema los requisitos variaron y resultaron más complejos de lo inicialmente previsto. Esta variabilidad y el amplio espectro de abstracción cubierto por la aplicación (desde el nivel más físico, con el controlador serie, hasta el nivel más abstracto, como puede ser la interfaz gráfica) ha resultado en un desafío muy completo y al mismo tiempo enriquecedor para el Proyecto de Fin de Carrera desarrollado, al ser una introducción adecuada al mundo de las aplicaciones de mediano y gran alcance.Ingeniería en Informátic

PeptideShaker Online: A User-Friendly Web-Based Framework for the Identification of Mass Spectrometry-Based Proteomics Data

Mass spectrometry-based proteomics is a high-throughput technology generating ever-larger amounts of data per project. However, storing, processing, and interpreting these data can be a challenge. A key element in simplifying this process is the development of interactive frameworks focusing on visualization that can greatly simplify both the interpretation of data and the generation of new knowledge. Here we present PeptideShaker Online, a user-friendly web-based framework for the identification of mass spectrometry-based proteomics data, from raw file conversion to interactive visualization of the resulting data. Storage and processing of the data are performed via the versatile Galaxy platform (through SearchGUI, PeptideShaker, and moFF), while the interaction with the results happens via a locally installed web server, thus enabling researchers to process and interpret their own data without requiring advanced bioinformatics skills or direct access to compute-intensive infrastructures. The source code, additional documentation, and a fully functional demo is available at https://github.com/barsnes-group/peptide-shaker-online.publishedVersio

PathwayMatcher: proteoform-centric network construction enables fine-granularity multi-omics pathway mapping

Background Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers (e.g., gene sets) in pathway knowledge bases. However, the isoform and posttranslational modification states of proteins are lost when converting input and pathways into gene-centric lists. Findings Based on the Reactome knowledge base, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input and outputs the possibly affected biochemical reactions, subnetworks, and pathways. Conclusions PathwayMatcher enables refining the network representation of pathways by including proteoforms defined as protein isoforms with posttranslational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity, and it becomes possible to distinguish interactions between different forms of the same protein.publishedVersio

Introducing the Brassica Information Portal: Towards integrating genotypic and phenotypic Brassica crop data [version 1; referees: 2 approved]

The Brassica Information Portal (BIP) is a centralised repository for Brassica phenotypic data. Trait data associated with Brassica research and breeding experiments conducted on Brassica crops, used as vegetables, for livestock fodder and biofuels, is hosted on the site, together with information on the experimental plant materials used, as well as trial design. BIP is an open access and open source project, built on the schema of CropStoreDB, and as such can provide trait data management strategies for any crop data. A new user interface and programmatic submission/retrieval system helps to simplify data access for scientists and breeders. BIP opens up the opportunity to apply big data analyses to data generated by the Brassica Research Community. Here, we present a short description of the current status of the repository

PeptideShaker Online: A User-Friendly Web-Based Framework for the Identification of Mass Spectrometry-Based Proteomics Data

Mass spectrometry-based proteomics is a high-throughput technology generating ever-larger amounts of data per project. However, storing, processing, and interpreting these data can be a challenge. A key element in simplifying this process is the development of interactive frameworks focusing on visualization that can greatly simplify both the interpretation of data and the generation of new knowledge. Here we present PeptideShaker Online, a user-friendly web-based framework for the identification of mass spectrometry-based proteomics data, from raw file conversion to interactive visualization of the resulting data. Storage and processing of the data are performed via the versatile Galaxy platform (through SearchGUI, PeptideShaker, and moFF), while the interaction with the results happens via a locally installed web server, thus enabling researchers to process and interpret their own data without requiring advanced bioinformatics skills or direct access to compute-intensive infrastructures. The source code, additional documentation, and a fully functional demo is available at https://github.com/barsnes-group/peptide-shaker-online

PathwayMatcher: proteoform-centric network construction enables fine-granularity multi-omics pathway mapping

Background Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers (e.g., gene sets) in pathway knowledge bases. However, the isoform and posttranslational modification states of proteins are lost when converting input and pathways into gene-centric lists. Findings Based on the Reactome knowledge base, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input and outputs the possibly affected biochemical reactions, subnetworks, and pathways. Conclusions PathwayMatcher enables refining the network representation of pathways by including proteoforms defined as protein isoforms with posttranslational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity, and it becomes possible to distinguish interactions between different forms of the same protein