Motivation: With many transgenic proteins introduced today, the ability to predict their potential allergenicity has become an important issue. Previous studies were based on either sequence similarity or the protein motifs identified from known allergen databases. The similarity-based approaches, although being able to produce high recalls, usually have low prediction precisions. Previous motif-based approaches have been shown to be able to improve the precisions on cross-validation experiments.
G-PRIMER, a web-based primer design program, has been developed to compute a minimal primer set specifically annealed to all the open reading frames in a given microbial genome. This program has been successfully used in the microarray experiment for analyzing the expression of genes in the Xanthomonas campestris genome.
As healthcare moves towards the implementation of Evidence-Based Medicine (EBM), Critically Appraised Topics (CATs) become useful in helping physicians to make clinical decisions. A number of academic and healthcare organizations have set up web-based CAT libraries. The primary objective of the presented work is to provide a one-stop search and download site that allows access to multiple CAT libraries. A web-based application, namely the CAT Crawler, was developed to serve physicians with an adequate access to available appraised topics on the Internet.
We present an algorithm to detect protein sub-structural motifs from primary sequence. The input to the algorithm is a set of aligned multiple protein sequences. It uses wavelet transforms to decompose protein sequences represented numerically by different indices (such as polarity, accessible surface area or electron-ion integration potentials of the amino acids). The numerical representation of a protein sequence has significant correlation with its biological activity, thus common motifs are expected to be observable from the wavelet spectrum.