WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results

Cluster analysis methods have been extensively researched, but the adoption of new methods is often hindered by technical barriers in their implementation and use. WebGimm is a free cluster analysis web-service, and an open source general purpose clustering web-server infrastructure designed to facilitate easy deployment of integrated cluster analysis servers based on clustering and functional annotation algorithms implemented in R. Integrated functional analyses and interactive browsing of both, clustering structure and functional annotations provides a complete analytical environment for cluster analysis and interpretation of results. The Java Web Start client-based interface is modeled after the familiar cluster/treeview packages making its use intuitive to a wide array of biomedical researchers. For biomedical researchers, WebGimm provides an avenue to access state of the art clustering procedures. For Bioinformatics methods developers, WebGimm offers a convenient avenue to deploy their newly developed clustering methods. WebGimm server, software and manuals can be freely accessed at http://ClusterAnalysis.org/

Benzo-fused Tri[8]annulenes as Molecular Models of Cubic Graphite

Cyclotrimerization of 9,10‐dibromo‐9,10‐dihydrodibenzo[3,4:7,8]cycloocta[1,2‐l]phenanthrene with potassium tert‐butoxide in the presence of a transition‐metal catalyst afforded two polycyclic aromatic hydrocarbon stereoisomers consisting of three cyclooctatetraene (COT) moieties connected via a central benzene ring. Both isomeric tri[8]annulenes were obtained selectively through the choice of the catalyst: The α,α,α‐form (Ru catalyst) displayed a threefold symmetrywith the COT subunits forming the side walls of a (chiral) molecular cup. In the thermodynamically more stable α,α,β‐isomer (Pd catalyst), one of the three boat‐shaped COTs was flipped over and faced the opposite molecular hemisphere with respect to the central benzene ring as evidenced by crystal structure analysis. Both title compounds are small segments of “cubic graphite”, an elusive carbon allotrope

TLR9-Dependent and Independent Pathways Drive Activation of the Immune System by Propionibacterium Acnes

Propionibacterium acnes is usually a relatively harmless commensal. However, under certain, poorly understood conditions it is implicated in the etiology of specific inflammatory diseases. In mice, P. acnes exhibits strong immunomodulatory activity leading to splenomegaly, intrahepatic granuloma formation, hypersensitivity to TLR ligands and endogenous cytokines, and enhanced resistance to infection. All these activities reach a maximum one week after P. acnes priming and require IFN-γ and TLR9. We report here the existence of a markedly delayed (1–2 weeks), but phenotypically similar TLR9-independent immunomodulatory response to P. acnes. This alternative immunomodulation is also IFN-γ dependent and requires functional MyD88. From our experiments, a role for MyD88 in the IFN-γ-mediated P. acnes effects seems unlikely and the participation of the known MyD88-dependent receptors, including TLR5, Unc93B-dependent TLRs, IL-1R and IL-18R in the development of the alternative response has been excluded. However, the crucial role of MyD88 can partly be attributed to TLR2 and TLR4 involvement. Either of these two TLRs, activated by bacteria and/or endogenously generated ligands, can fulfill the required function. Our findings hint at an innate immune sensitizing mechanism, which is potentially operative in both infectious and sterile inflammatory disorders

Genomics Portals: integrative web-platform for mining genomics data

<p>Abstract</p> <p>Background</p> <p>A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems.</p> <p>Results</p> <p>Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis.</p> <p>Conclusion</p> <p>The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at <url>http://GenomicsPortals.org</url>.</p

A Simple Method for Analyzing Exome Sequencing Data Shows Distinct Levels of Nonsynonymous Variation for Human Immune and Nervous System Genes

To measure the strength of natural selection that acts upon single nucleotide variants (SNVs) in a set of human genes, we calculate the ratio between nonsynonymous SNVs (nsSNVs) per nonsynonymous site and synonymous SNVs (sSNVs) per synonymous site. We transform this ratio with a respective factor f that corrects for the bias of synonymous sites towards transitions in the genetic code and different mutation rates for transitions and transversions. This method approximates the relative density of nsSNVs (rdnsv) in comparison with the neutral expectation as inferred from the density of sSNVs. Using SNVs from a diploid genome and 200 exomes, we apply our method to immune system genes (ISGs), nervous system genes (NSGs), randomly sampled genes (RSGs), and gene ontology annotated genes. The estimate of rdnsv in an individual exome is around 20% for NSGs and 30–40% for ISGs and RSGs. This smaller rdnsv of NSGs indicates overall stronger purifying selection. To quantify the relative shift of nsSNVs towards rare variants, we next fit a linear regression model to the estimates of rdnsv over different SNV allele frequency bins. The obtained regression models show a negative slope for NSGs, ISGs and RSGs, supporting an influence of purifying selection on the frequency spectrum of segregating nsSNVs. The y-intercept of the model predicts rdnsv for an allele frequency close to 0. This parameter can be interpreted as the proportion of nonsynonymous sites where mutations are tolerated to segregate with an allele frequency notably greater than 0 in the population, given the performed normalization of the observed nsSNV to sSNV ratio. A smaller y-intercept is displayed by NSGs, indicating more nonsynonymous sites under strong negative selection. This predicts more monogenically inherited or de-novo mutation diseases that affect the nervous system