UNLABELLED: WebAllergen is a web server that predicts the potential allergenicity of proteins. The query protein will be compared against a set of prebuilt allergenic motifs that have been obtained from 664 known allergen proteins. The query will also be compared with known allergens that do not have detectable allergenic motifs. Moreover, users are allowed to upload their own allergens as alternative training sequences on which a new set of allergenic motifs will be built. The query sequences can also be compared with these motifs. AVAILABILITY: http://weballergen.bii.a-star.edu.sg/

BACKGROUND: We observe two trends in bioinformatics: (i) analyses are increasing in complexity, often requiring several applications to be run as a workflow; and (ii) multiple CPU clusters and Grids are available to more scientists. The traditional solution to the problem of running workflows across multiple CPUs required programming, often in a scripting language such as perl. Programming places such solutions beyond the reach of many bioinformatics consumers. RESULTS: We present Wildfire, a graphical user interface for constructing and running workflows. Wildfire borrows user interface features from Jemboss and adds a drag-and-drop interface allowing the user to compose EMBOSS (and other) programs into workflows. For execution, Wildfire uses GEL, the underlying workflow execution engine, which can exploit available parallelism on multiple CPU machines including Beowulf-class clusters and Grids. CONCLUSION: Wildfire simplifies the tasks of constructing and executing bioinformatics workflows.

MOTIVATION: Approximate tandem repeats (ATR) occur frequently in the genomes of organisms, and are a source of polymorphisms observed in individuals, and thus are of interest to those studying genetic disorders. Though extensive work has been done in order to identify ATRs, there are inherent limitations with the current approaches in terms of the number of pattern sizes that can be searched or the size of the input length. RESULTS: This paper describes (1) a new algorithm which exhaustively finds all variable-length ATRs in a genomic sequence and (2) a precise description of, and an algorithm to significantly reduce, redundancy in the output. Our ATR definition is parameterized by a mismatch ratio p which allows for more mismatches in longer tandem repeats (and fewer in shorter). Furthermore, our algorithm is embarrassingly parallel and thus can attain near-linear speed-up on Beowulf clusters. We present results of our algorithm applied to sequences of widely differing lengths (from genes to chromosomes). AVAILABILITY: Source and binaries are available on request.