BACKGROUND: Although there are many studies on the characteristics of miRNA-mRNA interactions using miRNA and mRNA sequencing data, the complexity of the change of the correlation coefficients and expression values of the miRNA-mRNA pairs between tumor and normal samples is still not resolved, and this hinders the potential clinical applications. There is an urgent need to develop innovative methodologies and tools that can characterize and visualize functional consequences of cancer risk gene and miRNA pairs while analyzing the tumor and normal samples simultaneously. RESULTS: web server integrates and displays the mRNA and miRNA gene annotation information, signaling cascade pathways and direct cancer association between miRNAs and mRNAs. Functional annotation and gene regulatory information can be directly retrieved from our web server, which can help users quickly identify significant interaction sub-network and report possible disease or cancer association. The tool can identify pivotal miRNAs or mRNAs that contribute to the complexity of cancer, while engaging modern next-generation sequencing technology to analyze the tumor and normal samples concurrently. We compared our tools with other visualization tools. CONCLUSION: serves as a multitasking platform in which users can identify significant interaction clusters and retrieve functional and cancer-associated information for miRNA-mRNA pairs between tumor and normal samples. Our tool is applicable across a range of diseases and cancers and has advantages over existing tools.

BACKGROUND: MicroRNAs (miRNA) are short nucleotides that interact with their target genes through 3' untranslated regions (UTRs). The Cancer Genome Atlas (TCGA) harbors an increasing amount of cancer genome data for both tumor and normal samples. However, there are few visualization tools focusing on concurrently displaying important relationships and attributes between miRNAs and mRNAs of both cancer tumor and normal samples. Moreover, a deep investigation of miRNA-mRNA target and biological relationships across multiple cancer types by integrating web-based analysis has not been thoroughly conducted. RESULTS: We developed an interactive visualization tool called MMiRNA-Viewer that can concurrently present the co-relationships of expression between miRNA-mRNA pairs of both tumor and normal samples into a single graph. The input file of MMiRNA-Viewer contains the expression information including fold changes between normal and tumor samples for mRNAs and miRNAs, the correlation between mRNA and miRNA, and the predicted target relationship by a number of databases. Users can also load their own input data into MMiRNA-Viewer and visualize and compare detailed information about cancer-related gene expression changes, and also changes in the expression of transcription-regulating miRNAs. To validate the MMiRNA-Viewer, eight types of TCGA cancer datasets with both normal and control samples were selected in this study and three filter steps were applied subsequently. We performed Gene Ontology (GO) analysis for genes available in final selected 238 pairs and also for genes in the top 5 % (95 percentile) for each of eight cancer types to report a significant number of genes involved in various biological functions and pathways. We also calculated various centrality measurement matrices for the largest connected component(s) in each of eight cancers and reported top genes and miRNAs with high centrality measurements. CONCLUSIONS: With its user-friendly interface, dynamic visualization and advanced queries, we also believe MMiRNA-Viewer offers an intuitive approach for visualizing and elucidating co-relationships between miRNAs and mRNAs of both tumor and normal samples. We suggest that miRNA and mRNA pairs with opposite fold changes of their expression and with inverted correlation values between tumor and normal samples might be most relevant for explaining the decoupling of mRNAs and their targeting miRNAs in tumor samples for certain cancer types.

Component middleware is popular for enterprise distributed systems because it provides effective reuse of the core intellectual property (i.e., the "business logic"). Component-based enterprise distributed real-time and embedded (DRE) systems, however, incur new integration problems associated with component configuration and deployment. New research is therefore needed to minimize the gap between the development and deployment/configuration of components, so that deployment and configuration strategies can be evaluated well before system integration. This paper uses an industrial case study from the domain of shipboard computing to show how system execution modeling tools can provide software and system engineers with quantitative estimates of system bottlenecks and performance characteristics to help evaluate the performance of component-based enterprise DRE systems and reduce time/effort in the integration phase. The results from our case study show the benefits of system execution modeling tools and pinpoint where more work is needed

Abstract Motivation: Most molecular phylogenies are based on sequence alignments. Consequently, they fail to account for modes of sequence evolution that involve frequent insertions or deletions. Here we present a method for generating accurate gene and species phylogenies from whole genome sequence that makes use of short character string matches not placed within explicit alignments. In this work, the singular value decomposition of a sparse tetrapeptide frequency matrix is used to represent the proteins of organisms uniquely and precisely as vectors in a high-dimensional space. Vectors of this kind can be used to calculate pairwise distance values based on the angle separating the vectors, and the resulting distance values can be used to generate phylogenetic trees. Protein trees so derived can be examined directly for homologous sequences. Alternatively, vectors defining each of the proteins within an organism can be summed to provide a vector representation of the organism, which is then used to generate species trees. Results: Using a large mitochondrial genome dataset, we have produced species trees that are largely in agreement with previously published trees based on the analysis of identical datasets using different methods. These trees also agree well with currently accepted phylogenetic theory. In principle, our method could be used to compare much larger bacterial or nuclear genomes in full molecular detail, ultimately allowing accurate gene and species relationships to be derived from a comprehensive comparison of complete genomes. In contrast to phylogenetic methods based on alignments, sequences that evolve by relative insertion or deletion would tend to remain recognizably similar. Availability: Both the program used to convert properly formatted sequence files into sparse n-gram matrices (aacode3) and the program used to generate PHYLIP compatible pairwise distance matrices from the Singular Value Decomposition (SVD) output (cosdist) are available at http://mama.indstate.edu/user/stuart. The SVD package is available at http://www.netlib.org/svdpack/index.html, and the PHYLIP package is available at http://evolution.genetics.washington.edu/phylip.html. Contact: [email protected] * To whom correspondence should be addressed.