MOTIVATION: Quantitative and qualitative assessment of biological data often produces small essential recurrent networks, containing 3-5 components called network motifs. In this context, model solutions for small network motifs represent very high interest. RESULTS: Software package NetExplore has been created in order to generate, classify and analyze solutions for network motifs including up to six network components. NetExplore allows plotting and visualization of the solution's phase spaces and bifurcation diagrams. AVAILABILITY AND IMPLEMENTATION: The current version of NetExplore has been implemented in Perl-CGI and is accessible at the following locations: http://line.bioinfolab.net/nex/NetExplore.htm and http://nex.autosome.ru/nex/NetExplore.htm.

MOTIVATION: Animal development depends on localized patterns of gene expression. Whole-genome methods permit the global identification of differential expression patterns. However, most gene-expression-clustering methods focus on the analysis of entire expression profiles, rather than temporal segments or time windows. RESULTS: In the current study, local clustering of temporal time windows was applied to developing embryos of the fruitfly, Drosophila melanogaster. Large-scale developmental events, involving temporal activation of hundreds of genes, were identified as discrete gene clusters. The time-duration analysis revealed six temporal waves of coherent gene expression during Drosophila embryogenesis. The most powerful expression waves preceded major morphogenetic movements, such as germ band elongation and dorsal closure. These waves of gene expression coincide with the inhibition of maternal transcripts during early development, the specification of ectoderm, differentiation of the nervous system, differentiation of the digestive tract, deposition of the larval cuticle and the reorganization of the cytoskeleton during global morphogenetic events. We discuss the implications of these findings with respect to the gene regulatory networks governing Drosophila development. AVAILABILITY: Data and software are available from the UC Berkeley web resource http://flydev.berkeley.edu/cgi-bin/GTEM/dmap_dm-ag/index_dmap.htm

BACKGROUND: Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution. RESULTS: We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (Saccharomyces cerevisiae) and fission (Schizosaccharomyces pombe) yeast, which are separated by more then approximately 400 myr of evolution. We found that the global alignment (time warping) properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment. CONCLUSION: Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.

Abstract ClusterDraw is a program aimed to identification of binding sites and binding-site clusters. Major difference of the ClusterDraw from existing tools is its ability to scan a wide range of parameter values and weigh statistical significance of all possible clusters, smaller than a selected size. The program produces graphs along with decorated FASTA files. ClusterDraw web server is available at the following URL: http://flydev.berkeley.edu/cgi-bin/cld/submit.cgi Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

Formation of spatial gene expression patterns in development depends on transcriptional responses mediated by gene control regions, enhancers. Here, we explore possible responses of enhancers to overlapping gradients of antagonistic transcriptional regulators in the Drosophila embryo. Using quantitative models based on enhancer structure, we demonstrate how a pair of antagonistic transcription factor gradients with similar or even identical spatial distributions can lead to the formation of distinct gene expression domains along the embryo axes. The described mechanisms are sufficient to explain the formation of the anterior and the posterior knirps expression, the posterior hunchback expression domain, and the lateral stripes of rhomboid expression and of other ventral neurogenic ectodermal genes. The considered principles of interaction between antagonistic gradients at the enhancer level can also be applied to diverse developmental processes, such as domain specification in imaginal discs, or even eyespot pattern formation in the butterfly wing.

MOTIVATION: Genomic sequences are highly redundant and contain many types of repetitive DNA. Fuzzy tandem repeats (FTRs) are of particular interest. They are found in regulatory regions of eukaryotic genes and are reported to interact with transcription factors. However, accurate assessment of FTR occurrences in different genome segments requires specific algorithm for efficient FTR identification and classification. RESULTS: We have obtained formulas for P-values of FTR occurrence and developed an FTR identification algorithm implemented in TandemSWAN software. Using TandemSWAN we compared the structure and the occurrence of FTRs with short period length (up to 24 bp) in coding and non-coding regions including UTRs, heterochromatic, intergenic and enhancer sequences of Drosophila melanogaster and Drosophila pseudoobscura. Tandems with period three and its multiples were found in coding segments, whereas FTRs with periods multiple of six are overrepresented in all non-coding segment. Periods equal to 5-7 and 11-14 were characteristic of the enhancer regions and other non-coding regions close to genes. AVAILABILITY: TandemSWAN web page, stand-alone version and documentation can be found at http://bioinform.genetika.ru/projects/swan/www/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Transcription regulatory regions in higher eukaryotes are often represented by cis-regulatory modules (CRM) and are responsible for the formation of specific spatial and temporal gene expression patterns. These extended, approximately 1 KB, regions are found far from coding sequences and cannot be extracted from genome on the basis of their relative position to the coding regions. RESULTS: To explore the feasibility of CRM extraction from a genome, we generated an original training set, containing annotated sequence data for most of the known developmental CRMs from Drosophila. Based on this set of experimental data, we developed a strategy for statistical extraction of cis-regulatory modules from the genome, using exhaustive analysis of local word frequency (LWF). To assess the performance of our analysis, we measured the correlation between predictions generated by the LWF algorithm and the distribution of conserved non-coding regions in a number of Drosophila developmental genes. CONCLUSIONS: In most of the cases tested, we observed high correlation (up to 0.6-0.8, measured on the entire gene locus) between the two independent techniques. We discuss computational strategies available for extraction of Drosophila CRMs and possible extensions of these methods.