EBI databases and services

The EMBL Outstation-European Bioinformatics Institute (EBI) is a center for research and services in bioinformatics. It serves researchers in molecular biology, genetics, medicine, and agriculture from academia, and the agricultural, biotechnology, chemical, and pharmaceutical industries. The Institute manages and makes available databases of biological data including nucleic acid, protein sequences, and macromolecular structures. It provides to this community bioinformatics services relevant to molecular biology free of charge over the Internet. Some of these databases and services are described in this review. For more information, visit the EBI Web server at http://www.ebi.ac.uk/.     

Storage and retrieval of microarray data and open source microarray database software

Microarray technology has been widely adopted by researchers who use both home-made microarrays and microarrays purchased from commercial vendors. Associated with the adoption of this technology has been a deluge of complex data, both from the microarrays themselves, and also in the form of associated meta data, such as gene annotation information, the properties and treatment of biological samples, and the data transformation and analysis steps taken downstream. In addition, standards for annotation and data exchange have been proposed, and are now being adopted by journals and funding agencies alike. The coupling of large quantities of complex data with extensive and complex standards require all but the most small-scale of microarray users to have access to a robust and scaleable database with various tools. In this review, we discuss some of the desirable properties of such a database, and look at the features of several freely available alternatives.     

Bioinformatics software resources

This review looks at internet archives, repositories and lists for obtaining popular and useful biology and bioinformatics software. Resources include collections of free software, services for the collaborative development of new programs, software news media and catalogues of links to bioinformatics software and web tools. Problems with such resources arise from needs for continued curator effort to collect and update these, combined with less than optimal community support, funding and collaboration. Despite some problems, the available software repositories provide needed public access to many tools that are a foundation for analyses in bioscience research efforts.     

The Path to Enlightenment： Making Sense of Genomic and Proteomic Information

Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.     

Farm animal genome databases

The requirements for bioinformatics resources to support genome research in farm animals is reviewed.The resources developed to meet these needs are described. Resource databases and associated tools have been developed to handle experimental data. Several of these systems serve the needs of multinational collaborations. Genome databases have been established to provide contemporary summaries of the status of genome maps in a range of farm and domestic animals along with experimental details and citations. New resources and tools will be required to address the informatics needs of emerging technologies such as microarrays. However, continued investment is also required to maintain the currency and utility of the current systems, especially the genome databases.     

The RNA structure alignment ontology

Multiple sequence alignments are powerful tools for understanding the structures, functions, and evolutionary histories of linear biological macromolecules (DNA, RNA, and proteins), and for finding homologs in sequence databases. We address several ontological issues related to RNA sequence alignments that are informed by structure. Multiple sequence alignments are usually shown as two-dimensional (2D) matrices, with rows representing individual sequences, and columns identifying nucleotides from different sequences that correspond structurally, functionally, and/or evolutionarily. However, the requirement that sequences and structures correspond nucleotide-by-nucleotide is unrealistic and hinders representation of important biological relationships. High-throughput sequencing efforts are also rapidly making 2D alignments unmanageable because of vertical and horizontal expansion as more sequences are added. Solving the shortcomings of traditional RNA sequence alignments requires explicit annotation of the meaning of each relationship within the alignment. We introduce the notion of “correspondence,” which is an equivalence relation between RNA elements in sets of sequences as the basis of an RNA alignment ontology. The purpose of this ontology is twofold: first, to enable the development of new representations of RNA data and of software tools that resolve the expansion problems with current RNA sequence alignments, and second, to facilitate the integration of sequence data with secondary and three-dimensional structural information, as well as other experimental information, to create simultaneously more accurate and more exploitable RNA alignments.     

New approaches towards integrated proteomic databases and depositories

Since the publication of the human genome, two key points have emerged. First, it is still not certain which regions of the genome code for proteins. Second, the number of discrete protein-coding genes is far fewer than the number of different proteins. Proteomics has the potential to address some of these postgenomic issues if the obstacles that we face can be overcome in our efforts to combine proteomic and genomic data. There are many challenges associated with high-throughput and high-output proteomic technologies. Consequently, for proteomics to continue at its current growth rate, new approaches must be developed to ease data management and data mining. Initiatives have been launched to develop standard data formats for exchanging mass spectrometry proteomic data, including the Proteomics Standards Initiative formed by the Human Proteome Organization. Databases such as SwissProt and Uniprot are publicly available repositories for protein sequences annotated for function, subcellular location and known potential post-translational modifications. The availability of bioinformatics solutions is crucial for proteomics technologies to fulfil their promise of adding further definition to the functional output of the human genome. The aim of the Oxford Genome Anatomy Project is to provide a framework for integrating molecular, cellular, phenotypic and clinical information with experimental genetic and proteomics data. This perspective also discusses models to make the Oxford Genome Anatomy Project accessible and beneficial for academic and commercial research and development.     

Current progress in computational metabolomics

Being a relatively new addition to the 'omics' field, metabolomics is still evolving its own computational infrastructure and assessing its own computational needs. Due to its strong emphasis on chemical information and because of the importance of linking that chemical data to biological consequences, metabolomics must combine elements of traditional bioinformatics with traditional cheminformatics. This is a significant challenge as these two fields have evolved quite separately and require very different computational tools and skill sets. This review is intended to familiarize readers with the field of metabolomics and to outline the needs, the challenges and the recent progress being made in four areas of computational metabolomics: (i) metabolomics databases; (ii) metabolomics LIMS; (iii) spectral analysis tools for metabolomics and (iv) metabolic modeling.     

Bioinformatics and data mining in proteomics

Proteomic studies involve the identification as well as qualitative and quantitative comparison of proteins expressed under different conditions, and elucidation of their properties and functions, usually in a large-scale, high-throughput format. The high dimensionality of data generated from these studies will require the development of improved bioinformatics tools and data-mining approaches for efficient and accurate data analysis of biological specimens from healthy and diseased individuals. Mining large proteomics data sets provides a better understanding of the complexities between the normal and abnormal cell proteome of various biological systems, including environmental hazards, infectious agents (bioterrorism) and cancers. This review will shed light on recent developments in bioinformatics and data-mining approaches, and their limitations when applied to proteomics data sets, in order to strengthen the interdependence between proteomic technologies and bioinformatics tools.     

The psychopathological phenotype of velo-cardio-facial syndrome

Velo-cardio-facial syndrome (VCFS) is mostly associated with deletions of chromosome 22q11, and is thought to be characterized by an increased frequency of major psychiatric disorders. Sixteen patients adults with VCFS and psychiatric symptoms were evaluated using a semi-structured investigation of history, symptoms, signs and behaviour. All available data were used in consensus meetings to obtain a classifiable diagnostic category. In contrast to other reports, no categorical diagnosis could be established. Instead, a quite specific psychological, behavioural and psychopathological constellation emerged that should most adequately be denominated as a VCFS-psychiatric syndrome. It is concluded that VCFS is associated with a specific psychopathological syndrome.