Background Detailed information on DNA-binding transcription factors (the key players in
October 13, 2017
Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the Rog projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides CGP 57380 IC50 a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to predict putative contradictions or further gene regulatory interactions. Furthermore, it integrates protein clusters by means of heuristically solving the weighted CGP 57380 IC50 graph cluster editing problem. In addition, it provides Web Service based access to up to date gene annotation data from GenDB. Conclusion The release 4.0 of CoryneRegNet is a comprehensive system for the integrated analysis of procaryotic gene regulatory networks. It is a versatile systems biology platform to support the efficient and large-scale analysis of transcriptional regulation of gene expression in microorganisms. It is publicly available at http://www.CoryneRegNet.DE. Background Recently several whole-genome sequencing projects have generated huge amounts of data related to various microorganisms including gene and protein sequences and their functional annotations. These annotations can be performed, stored and analyzed with tools like e.g. GenDB . In order to handle changing environmental circumstances and to maintain growth and survival, the genes activity varies under different conditions. One major goal in systems biology is to understand the process of their transcriptional regulation. The application of post-genomic analysis techniques to bacterial genome sequences provides knowledge to encoded proteins involved in the gene regulation. Microarray experiments can be used to study the expression of genes and the results can be stored and analyzed using tools like EMMA . This data along with literature-derived knowledge on the regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of corynebacterial cells that allow systematic analysis of network behavior in response to changing environmental conditions. [3-7] Besides pathogenic corynebacterial species of medical importance, like C. diphtheriae and C. jeikeium, other corynebacteria like C. glutamicum and C. efficiens are traditionally used in biotechnological production processes. We previously designed CoryneRegNet, which is an ontology-based data warehouse implemented to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria and Escherichia coli. [8,9] It is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using an ontology-based data structure. We integrated a fast and statistically sound method (PoSSuMsearch ) to predict transcription factor binding CGP 57380 IC50 site motifs within and across species. It is the only available software package that is fast enough to provide interactive response times for large-scale PSSM searches and at the same time integrates exact statistics for p-value computations. Reconstructed regulatory networks can be visualized on a web interface and as graphs. Special graph layout algorithms have been developed and implemented to facilitate the comparison of gene regulatory networks across species. This is can be very benefitial for studying gene regulatory networks, as shown e.g. in [11-13]. A related system is RegulonDB . It focuses on E. coli, and so far lacks tools essential for regulatory network reconstruction and analysis such as binding site motif matching, protein cluster calculation, and homology detection. It furthermore just provides very simple network visualization and no network comparison and analysis features. Another existing system is PRODORIC , which has a comprehensive goal, but for most procaryotes only CGP 57380 IC50 contains the available NCBI genome annotation and no or just little gene regulatory data. Further information on gene regulations is available about E. coli (as in RegulonDB), B. subtilis, and P. aeruginosa. It does not provide the network visualization and comparison capabilities of CoryneRegNet, and its motif matching.