%0 Journal Article %J BMC Bioinformatics %D 2019 %T PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources. %A Perez-Gil, Daniel %A Lopez, Francisco J %A Dopazo, Joaquin %A Marin-Garcia, Pablo %A Rendon, Augusto %A Medina, Ignacio %K Computational Biology %K Databases, Factual %K Software %K User-Computer Interface %X

BACKGROUND: Biological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data accessibility and integration. To handle the growing necessity of unification, CellBase was created as an integrative solution. CellBase provides a centralized NoSQL database containing biological information from different and heterogeneous sources. Access to this information is done through a RESTful web service API, which provides an efficient interface to the data.

RESULTS: In this work we present PyCellBase, a Python package that provides programmatic access to the rich RESTful web service API offered by CellBase. This package offers a fast and user-friendly access to biological information without the need of installing any local database. In addition, a series of command-line tools are provided to perform common bioinformatic tasks, such as variant annotation. CellBase data is always available by a high-availability cluster and queries have been tuned to ensure a real-time performance.

CONCLUSION: PyCellBase is an open-source Python package that provides an efficient access to heterogeneous biological information. It allows to perform tasks that require a comprehensive set of knowledge resources, as for example variant annotation. Queries can be easily fine-tuned to retrieve the desired information of particular biological features. PyCellBase offers the convenience of an object-oriented scripting language and provides the ability to integrate the obtained results into other Python applications and pipelines.

%B BMC Bioinformatics %V 20 %P 159 %8 2019 Mar 28 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/30922213?dopt=Abstract %R 10.1186/s12859-019-2726-4 %0 Journal Article %J BMC Bioinformatics %D 2017 %T VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy. %A Juanes, José M %A Gallego, Asunción %A Tárraga, Joaquín %A Chaves, Felipe J %A Marin-Garcia, Pablo %A Medina, Ignacio %A Arnau, Vicente %A Dopazo, Joaquin %K Base Sequence %K Genetic Therapy %K Genetic Vectors %K High-Throughput Nucleotide Sequencing %K Humans %K Internet %K User-Computer Interface %K Virus Integration %X

BACKGROUND: The possibility of integrating viral vectors to become a persistent part of the host genome makes them a crucial element of clinical gene therapy. However, viral integration has associated risks, such as the unintentional activation of oncogenes that can result in cancer. Therefore, the analysis of integration sites of retroviral vectors is a crucial step in developing safer vectors for therapeutic use.

RESULTS: Here we present VISMapper, a vector integration site analysis web server, to analyze next-generation sequencing data for retroviral vector integration sites. VISMapper can be found at: http://vismapper.babelomics.org .

CONCLUSIONS: Because it uses novel mapping algorithms VISMapper is remarkably faster than previous available programs. It also provides a useful graphical interface to analyze the integration sites found in the genomic context.

%B BMC Bioinformatics %V 18 %P 421 %8 2017 Sep 20 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/28931371?dopt=Abstract %R 10.1186/s12859-017-1837-z %0 Journal Article %J Nucleic acids research %D 2015 %T Babelomics 5.0: functional interpretation for new generations of genomic data. %A Alonso, Roberto %A Salavert, Francisco %A Garcia-Garcia, Francisco %A Carbonell-Caballero, José %A Bleda, Marta %A García-Alonso, Luz %A Sanchis-Juan, Alba %A Perez-Gil, Daniel %A Marin-Garcia, Pablo %A Sánchez, Rubén %A Cubuk, Cankut %A Hidalgo, Marta R %A Amadoz, Alicia %A Hernansaiz-Ballesteros, Rosa D %A Alemán, Alejandro %A Tárraga, Joaquín %A Montaner, David %A Medina, Ignacio %A Dopazo, Joaquin %K babelomics %K data integration %K gene set analysis %K interactome %K network analysis %K NGS %K RNA-seq %K Systems biology %K transcriptomics %X Babelomics has been running for more than one decade offering a user-friendly interface for the functional analysis of gene expression and genomic data. Here we present its fifth release, which includes support for Next Generation Sequencing data including gene expression (RNA-seq), exome or genome resequencing. Babelomics has simplified its interface, being now more intuitive. Improved visualization options, such as a genome viewer as well as an interactive network viewer, have been implemented. New technical enhancements at both, client and server sides, makes the user experience faster and more dynamic. Babelomics offers user-friendly access to a full range of methods that cover: (i) primary data analysis, (ii) a variety of tests for different experimental designs and (iii) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context. In addition to the public server, local copies of Babelomics can be downloaded and installed. Babelomics is freely available at: http://www.babelomics.org. %B Nucleic acids research %V 43 %P W117-W121 %8 2015 Apr 20 %G eng %U http://nar.oxfordjournals.org/content/43/W1/W117 %R 10.1093/nar/gkv384