BACKGROUND: With the growing amount of biomedical data available in public databases it has become increasingly important to annotate data in a consistent way in order to allow easy access to this rich source of information. Annotating the data using controlled vocabulary terms and ontologies makes it much easier to compare and analyze data from different sources. However, finding the correct controlled vocabulary terms can sometimes be a difficult task for the end user annotating these data. RESULTS: In order to facilitate the location of the correct term in the correct controlled vocabulary or ontology, the Ontology Lookup Service was created. However, using the Ontology Lookup Service as a web service is not always feasible, especially for researchers without bioinformatics support. We have therefore created a Java front end to the Ontology Lookup Service, called the OLS Dialog, which can be plugged into any application requiring the annotation of data using controlled vocabulary terms, making it possible to find and use controlled vocabulary terms without requiring any additional knowledge about web services or ontology formats. CONCLUSIONS: As a user-friendly open source front end to the Ontology Lookup Service, the OLS Dialog makes it straightforward to include controlled vocabulary support in third-party tools, which ultimately makes the data even more valuable to the biomedical community.

BACKGROUND: Proteomics is the study of the proteome, and is critical to the understanding of cellular processes. Two central and related tasks of proteomics are protein identification and protein characterization. Many small laboratories are interested in the characterization of a small number of proteins, e.g., how posttranslational modifications change under different conditions. RESULTS: We have developed a software tool called MassSorter for administrating and analyzing data from peptide mass fingerprinting experiments on proteins with known amino acid sequences. It is meant for small scale mass spectrometry laboratories that are interested in posttranslational modifications of known proteins. Several experiments can be compared simultaneously, and the matched and unmatched peak values are clearly indicated. The hits can be sorted according to m/z values (default) or according to the sequence of the protein. Filters defined by the user can mark autolytic protease peaks and other contaminating peaks (keratins, proteins co-migrating with the protein of interest, etc.). Unmatched peaks can be further analyzed for unexpected modifications by searches against a local version of the UniMod database. They can also be analyzed for unexpected cleavages, a highly useful feature for proteins that undergo maturation by proteolytic cleavage, creating new N- or C-terminals. Additional tools exist for visualization of the results, like sequence coverage, accuracy plots, different types of statistics, 3D models, etc. The program and a tutorial are freely available for academic users at http://www.bioinfo.no/software/massSorter. CONCLUSION: MassSorter has a number of useful features that can promote the analysis and administration of MS-data.

BACKGROUND: As genomes evolve after speciation, gene content, coding sequence, gene expression, and splicing all diverge with time from ancestors with close relatives. A minimum evolution general method for continuous character analysis in a phylogenetic perspective is presented that allows for reconstruction of ancestral character states and for measuring along branch evolution. RESULTS: A software package for reconstruction of continuous character traits, like relative gene expression levels or alternative splice site usage data is presented and is available for download at http://www.rossnes.org/phyrex. This program was applied to a primate gene expression dataset to detect transcription factor binding sites that have undergone substitution, potentially having driven lineage-specific differences in gene expression. CONCLUSION: Systematic analysis of lineage-specific evolution is becoming the cornerstone of comparative genomics. New methods, like phyrex, extend the capabilities of comparative genomics by tracing the evolution of additional biomolecular processes.

MOTIVATION: Radiation Hybrid Mapping (RHM) is a technique used to order a set of markers on a genome and estimating physical distances between them. RHM provides information on marker placement independent from other methods such as sequencing, and can therefore be used for example in genome sequencing to help ordering contigs. A radiation hybrid framework can be constructed by choosing a set of markers so that the chromosome coverage is good and so that the markers can be ordered with high confidence. Automatically constructing RHM frameworks is a computationally challenging problem. RESULTS: We have developed a new method for constructing radiation hybrid frameworks. Given a relatively large set of markers for a chromosome, the algorithm aims to select an ordered subset that makes up a framework, and that contains as many markers as possible. The algorithm has a time complexity that is better than any of the existing methods that we are aware of. Furthermore, we propose a method for comparing if two frameworks are consistent, giving a visual presentation as well as quantitative measures of how well the two frameworks agree. Applying our method on marker sets from 22 human chromosomes and comparing the resulting frameworks with previously published frameworks, we demonstrate that our automatic method efficiently constructs frameworks with good coverage of each chromosome and with high degree of agreement on the marker ordering.

MOTIVATION: Many of the most interesting functional and evolutionary relationships among proteins are so ancient that they cannot be reliably detected through sequence analysis and are apparent only through a comparison of the tertiary structures. The conserved features can often be described as structural motifs consisting of a few single residues or Secondary Structure (SS) elements. Confidence in such motifs is greatly boosted when they are found in more than a pair of proteins. RESULTS: We describe an algorithm for the automatic discovery of recurring patterns in protein structures. The patterns consist of individual residues having a defined order along the protein's backbone that come close together in the structure and whose spatial conformations are similar. The residues in a pattern need not be close in the protein's sequence. The work described in this paper builds on an earlier reported algorithm for motif discovery. This paper describes a significant improvement of the algorithm which makes it very efficient. The improved efficiency allows us to use it for doing unsupervised learning of patterns occurring in small subsets in a large set of structures, a non-redundant subset of the Protein Data Bank (PDB) database of all known protein structures.