The ISB Cancer Genomics Cloud: A Flexible Cloud-Based Platform for Cancer Genomics Research.

The ISB Cancer Genomics Cloud (ISB-CGC) is one of three pilot projects funded by the National Cancer Institute to explore new approaches to computing on large cancer datasets in a cloud environment. With a focus on Data as a Service, the ISB-CGC offers multiple avenues for accessing and analyzing The Cancer Genome Atlas, TARGET, and other important references such as GENCODE and COSMIC using the Google Cloud Platform. The open approach allows researchers to choose approaches best suited to the task at hand: from analyzing terabytes of data using complex workflows to developing new analysis methods in common languages such as Python, R, and SQL; to using an interactive web application to create synthetic patient cohorts and to explore the wealth of available genomic data. Links to resources and documentation can be found at www.isb-cgc.or

BioTapestry now provides a web application and improved drawing and layout tools [version 1; referees: 3 approved]

Gene regulatory networks (GRNs) control embryonic development, and to understand this process in depth, researchers need to have a detailed understanding of both the network architecture and its dynamic evolution over time and space. Interactive visualization tools better enable researchers to conceptualize, understand, and share GRN models. BioTapestry is an established application designed to fill this role, and recent enhancements released in Versions 6 and 7 have targeted two major facets of the program. First, we introduced significant improvements for network drawing and automatic layout that have now made it much easier for the user to create larger, more organized network drawings. Second, we revised the program architecture so it could continue to support the current Java desktop Editor program, while introducing a new BioTapestry GRN Viewer that runs as a JavaScript web application in a browser. We have deployed a number of GRN models using this new web application. These improvements will ensure that BioTapestry remains viable as a research tool in the face of the continuing evolution of web technologies, and as our understanding of GRN models grows

Comparative Genomics of Rice and Arabidopsis. Analysis of 727 Cytochrome P450 Genes and Pseudogenes from a Monocot and a Dicot

Data mining methods have been used to identify 356 Cyt P450 genes and 99 related pseudogenes in the rice (Oryza sativa) genome using sequence information available from both the indica and japonica strains. Because neither of these genomes is completely available, some genes have been identified in only one strain, and 28 genes remain incomplete. Comparison of these rice genes with the 246 P450 genes and 26 pseudogenes in the Arabidopsis genome has indicated that most of the known plant P450 families existed before the monocot-dicot divergence that occurred approximately 200 million years ago. Comparative analysis of P450s in the Pinus expressed sequence tag collections has identified P450 families that predated the separation of gymnosperms and flowering plants. Complete mapping of all available plant P450s onto the Deep Green consensus plant phylogeny highlights certain lineage-specific families maintained (CYP80 in Ranunculales) and lineage-specific families lost (CYP92 in Arabidopsis) in the course of evolution

TLR2-dependent Modulation of Osteoclastogenesis by Porphyromonas gingivalis through Differential Induction of NFATc1 and NF-κB*

Osteolytic diseases, including rheumatoid arthritis, osteomyelitis, and periodontitis, are usually associated with bacterial infections. However, the precise mechanisms by which bacteria induce bone loss still remain unclear. Evidence exists that Toll-like receptor (TLR) signaling regulates both inflammation and bone metabolism and that the receptor activator of NF-κB ligand (RANKL) and its receptor RANK are the key regulators for bone remodeling and for the activation of osteoclasts. Here, we investigate the direct effects of the periodontal pathogen Porphyromonas gingivalis on osteoclast differentiation and show that P. gingivalis differentially modulates RANKL-induced osteoclast formation contingent on the state of differentiation of osteoclast precursors. In addition, although an optimal induction of cytokines by P. gingivalis is dependent on TLR2 and TLR4, as well as myeloid differentiation factor 88 and Toll/IL-1R domain-containing adaptor-inducing IFN-β, P. gingivalis utilizes TLR2/ myeloid differentiation factor 88 in modulating osteoclast differentiation. P. gingivalis modulates RANKL-induced osteoclast formation by differential induction of NFATc1 and c-Fos. More importantly, RANKL-mediated lineage commitment also has an impact on P. gingivalis-induced cytokine production. RANKL inhibits P. gingivalis-induced cytokine production by down-regulation of TLR/NF-κB and up-regulation of NFATc1. Our findings reveal novel aspects of the interactions between TLR and RANK signaling and provide a new model for understanding the mechanism underlying the pathogenesis of bacteria-mediated bone loss