One of the major challenges in the post-genomic era is to determine all DNA-binding transcription factors (TFs) and their regulatory binding sites (motifs) within the genomes. To discover the relationship between the motifs and changes in gene expression, we propose a new algorithm, co-miner (correlation miner). Correlation rules are generated based on the expression profiles of genes with significant expression change through the time course of gene expression. Thus, we may consider the change in gene expression to be causatively associated with the transcription binding sites in the upstream sequences. In addition, we introduce partition and constraint pushing techniques to improve the performance and demonstrate their effectiveness by our experiments. By applying co-miner to a yeast dataset, the relationships between motifs and gene expression revealed by co-miner are confirmed in the literature.

BACKGROUND: Understanding the regulatory processes that coordinate the cascade of gene expression leading to male gamete development has proven challenging. Research has been hindered in part by an incomplete picture of the regulatory elements that are both characteristic of and distinctive to the broad population of spermatogenically expressed genes. DESCRIPTION: K-SPMM, a database of murine Spermatogenic Promoters Modules and Motifs, has been developed as a web-based resource for the comparative analysis of promoter regions and their constituent elements in developing male germ cells. The system contains data on 7,551 genes and 11,715 putative promoter regions in Sertoli cells, spermatogonia, spermatocytes and spermatids. K-SPMM provides a detailed portrait of promoter site components, ranging from broad distributions of transcription factor binding sites to graphical illustrations of dimeric modules with respect to individual transcription start sites. Binding sites are identified through their similarities to position weight matrices catalogued in either the JASPAR or the TRANSFAC transcription factor archives. A flexible search function allows sub-populations of promoters to be identified on the basis of their presence in any of the four cell-types, their association with a list of genes or their component transcription-factor families. CONCLUSION: This system can now be used independently or in conjunction with other databases of gene expression as a powerful aid to research networks of co-regulation. We illustrate this with respect to the spermiogenically active protamine locus in which binding sites are predicted that align well with biologically foot-printed protein binding domains. AVAILABILITY: http://klab.med.wayne.edu/kspmm/

Abstract Motivation: Complementary DNA libraries can define the genetic constituents of specific cells and/or tissues. Their sequencing will illuminate the transcriptome but it is a monumental task requiring considerable resources. Results: We have employed a computational search in conjunction with a microarray-based strategy to alleviate the impediments of deriving a consensus of records that describe testis gene expression. This strategy identified 5681 unique testes-expressed genes of which 3265 were previously portrayed in the UniGene database. Interestingly, a total of 2416 novel testes-expressed genes were identified. This clearly demonstrates that microarrays can be used to rapidly discover a large number of new transcripts. Contact: [email protected] * To whom correspondence should be addressed at: Charlotte B. Failing Professor, 253 C.S. Mott Center, 275 East Hancock, Detroit, MI, 48201, USA.

This communication describes DNAView, a graphical tool for the visualization and printing of large nucleic acid sequences. DNAView uses color coding to compactly display genomic segments of up to 100 kb on a single printed page. The specific color schemes integrated into DNAView can highlight 'local aggregate' properties of large segments of DNA. We have also incorporated a confidence expression for the assigned sequence. This is represented by base color intensity that is proportional to the number of times that base was sequenced. Areas of interest, such as exons, introns, repetitive elements and splice sites, can be emphasized using overlays. The colored image can be saved in a standard TIFF image file format that may be imported and annotated by other application software.

The BIAS (Biological Image Analysis System) was developed to: (i) permit accurate entry and image processing of biological data; (ii) minimize the need for specialized hardware; and (iii) aid in the human genome mapping and other projects. The first mouse/cursor key-driven module was designed to be user interactive and readily accessible to many laboratories. It contains the DRSNDS programs which automate the entering of data in a systematic format. The types of data that can be entered utilizing this module are DNA-RNA gels from either a positive or negative Polaroid image, autoradiograms or biotinylated images from Southern, Northern and dot or slot blot hybridization analyses. The image is acquired using a video camera and then digitized for subsequent analysis. During the analysis graphical representations of the intermediate results are provided to assure user confidence. At any point within the program the user may obtain on-line help with the current task. The output displays the mol. wt of each individual component in the appropriate context. The present version of the program produces results comparable with a human interpreter for some data. Band shifting and optical density calculations are in a prototype form to permit evaluation of various techniques. Future work is directed at expanding the system's capabilities to interpret data from other biological analyses including DNA sequencing gels.