Example 3. To convert a list of Ensembl gene identiﬁers to their HGNC gene symbol, CellBase implements a way to retrieve cross references for an identiﬁer using the External references (xref) subcategory. We just need to specify the list of identiﬁers and the name of the database we want to convert these IDs to. The resulting query will look like this: http://ws.bioinfo.cipf.es/cellbase/rest/latest/hsa/feature/id/ ENSG00000011478,ENSG00000008382/xref?dbname= hgnc_symbol Example 4. To fetch the target genes for a particular miRNA like hsa-mir-150: http://ws.bioinfo.cipf.es/cellbase/rest/latest/hsa/regulatory /mirna_gene/hsa-mir-150/target Example 5. To download a diagram of a speciﬁc pathway: http://ws.bioinfo.cipf.es/cellbase/rest/latest/hsa/network/ pathway/Triacylglycerol%20biosynthesis/image Example 6. To obtain all available species, codes and genome assemblies: http://ws.bioinfo.cipf.es/cellbase/rest/latest/species Using CellBase RESTful web services CellBase RESTful web services have been implemented using HTTP GET method, so they can be accessed directly from any web browser. We have also developed a Perl client Command Line Interface that can query CellBase web services and can parse large ﬁles of identi- ﬁers. CellBase web services are also available through some applications developed in our department such as Genome Maps (http://genomemaps.org), RENATO (http://renato.bioinfo.cipf.es) or VARIANT (http:// variant.bioinfo.cipf.es), what proves the beneﬁts and potential of this implementation. OTHER TOOLS Despite other solutions could be apparently similar, they do not cover the wide variety of biological information included in CellBase. While some of them are quite restricted to speciﬁc biological content, others are more general but do not provide web services and often require a local installation. Several resources use the Distributed Annotation System (DAS) protocol (23) to export their data encoded in XML format, which is slower, larger and more difﬁcult to parse than simple text or JSON. Similar to CellBase RESTful web services, DAS can distribute biological information based on genome and protein annotations. However, DAS protocol cannot handle functional annotations or systems biology data, such as gene ontology terms or protein–protein interactions, as CellBase does. Some data- bases like Ensembl, HapMap or Interpro export their bio- logical information using tools like Biomart which also provide data through WEB services. This can be useful when querying information from a single database, but becomes a problem when users need to link data from several Biomart sources. CellBase facilitates more Nucleic Acids Research, 2012, Vol. 40, Web Server issue W613 complex data queries by integrating and linking together different biological sources. DISCUSSION In this work, we have designed and implemented CellBase, a database and a collection of RESTful web services that enable quick and easy access to heterogeneous biological information. By joining data from some of the most relevant resources and integrating them into a single standardized database, CellBase provides users with a homogeneous RESTful web service API, with no need to query or download different sources. The integration of RESTful web services technologies has represented a great advantage to provide a comfortable way to query and retrieve this biological information using URLs. CellBase can be freely accessed in several ways to accommodate different scenarios or users. Web services can be consumed programmatically from any computing language or from a web browser; moreover, a Perl client has also been developed. Biological information and metadata services have been implemented. Database and web servers’ infrastructure have been designed to provide a high-availability and high-performance solution. The database is maintained by a group of biologists and computer scientists. Regular updates will be carried out every few months as new data appear. More species and additional biological data will be also added since the database schema and RESTful web services have been designed to be scalable and cover all biological informa- tion requirements. CellBase has proven to be priceless in some of our projects such as Genome Maps, RENATO or VARIANT, and we are, currently, developing new applications using CellBase as a key part of their implementation. As more genomes are sequenced and more data are available, the access and transfer will become a critical problem. To solve these issues, we are working on moving database and WEB services to the cloud to be able to increase the physical resources. In addition, by doing this, different images would be installed in different geographic regions for faster data queries. The problem of data size is also affecting relational databases as they are approximating to the limit of data they can store in a single machine, to solve this problem are also exploring different solutions like NoSQL databases that allow to store some terabytes of data in a distributed way. Theses changes will be transparent to users as WEB services will remain unchanged. ACKNOWLEDGEMENTS The authors thank National Institute of Bioinformatics (www.inab.org) and the CIBER de Enfermedades Raras (CIBERER), both initiatives of the ISCIII, MICINN. FUNDING The Spanish (MICINN) Ministry of Science and Innovation [BIO2011-27069]; the Conselleria de