BACKGROUND: Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis. RESULTS: We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study. CONCLUSIONS: The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps.

MOTIVATION: A large proportion of the information found in public databases is not sufficiently cross-referenced. We developed genXref, an automated system for link inference, because embarking on a manual cross-referencing of genome data would require too much expensive human expertise. It uses information retrieval technology to generate links between objects of heterogeneous databases. RESULTS: GenXref was used to generate links between GDB genes and Genbank human sequences. It resulted in > 10,000 links with a precision of 83% and a recall of approximately 32%.

We present here a codification structure, entirely interfaced with the main packages for biomolecule database management, associated with a new search algorithm to retrieve quickly a sequence in a database. This system is derived from a method previously proposed for homology search in databanks with a preprocessed codification of an entire database in which all the overlapping subsequences of a specific length in a sequence were converted into a code and stored in a hash-coding file. This new algorithm is designed for an improved use of the codification. It is based on the recognition of the rarest strings which characterize the query sequence and the intersection of sorted lists read in the codification structure. The system is applicable to both nucleic acid and protein sequences and is used to find patterns in databanks or large sets of sequences. A few examples of applications are given. In addition, the comparison of our method with existing ones shows that this new approach speeds up the search for query patterns in large data sets.

This paper presents a method for the multiple alignment of a sequence set. The MASH algorithm uses a non-redundant database of common motifs and an 'alignment priority' criterion that depends on the length and the occurrence frequency of the patterns in the set of sequences. This user-defined criterion allows the determination of the series of the patterns to be aligned. This program is applied to a fragment of envelope gene env gp120 for 20 isolates of the immunodeficiency virus. The multiplicity of alignments obtained by modifying the criterion parameters reveals different aspects of similarity between the sequences.

Phillipe Dessen, Christian Fondrat, Claire Valencien, Claude Mugnier; BISANCE: A French service for access to biomolecular sequence databases, Bioinformati

We have developed a new algorithm 'Complete sentences compatibility' (CSC) which uses single and double digestion fragments to rapidly determine restriction maps of circular DNA. From possible combinations of fragments of each simple digestion, which we call 'sentences of decomposition', we construct a restriction map which combines the sentences while taking into account compatibility rules. The algorithm can also deal with experimental errors of fragment weight and can suggest solutions that account for non-readable bands (fragments of zero length or multiple bands) on the gel. Because experiments using pairs of restrictive enzymes often result in multiple solutions, a complementary algorithm tries to reduce the number of proposed solutions by establishing consensus maps. The restriction map construction algorithm was tested on real cases, some containing more than fifteen fragments. Execution times range from 1-10 s on an IBM PC compatible microcomputer.

A computer program has been written in FORTRAN 77 to locate on a protein sequence a region with optimum length and limited degeneracy in order to design artificial oligonucleotide probes for use in molecular cloning. In addition the program checks for regions of homology between this probe and any other base sequence found in nucleotide sequence data banks. There are options in the program to eliminate rare codons or to make preferential choices of bases in order to minimize the degeneracy of probes.