The Syntheses of Benzo-(2.2)-Paracyclophane, 2, 15-Dithia-(3.3)-Napthalenophane, and Hexamethylbenzene Dichloride

The purpose of this study was the preparation by a novel approach of benzo-(2.2)-paracyclophane. Also synthesized were the syn-and anti-isomers of 2,15-dithia (3.3)- napthalenophane. The results of these syntheses are supported by spectral studies. In preparation for future study of the ruthenium complexes of these cyclophanes, hexamethylbenzeruthenium dichloride was also synthesized

Genomes as geography: using GIS technology to build interactive genome feature maps

BACKGROUND: Many commonly used genome browsers display sequence annotations and related attributes as horizontal data tracks that can be toggled on and off according to user preferences. Most genome browsers use only simple keyword searches and limit the display of detailed annotations to one chromosomal region of the genome at a time. We have employed concepts, methodologies, and tools that were developed for the display of geographic data to develop a Genome Spatial Information System (GenoSIS) for displaying genomes spatially, and interacting with genome annotations and related attribute data. In contrast to the paradigm of horizontally stacked data tracks used by most genome browsers, GenoSIS uses the concept of registered spatial layers composed of spatial objects for integrated display of diverse data. In addition to basic keyword searches, GenoSIS supports complex queries, including spatial queries, and dynamically generates genome maps. Our adaptation of the geographic information system (GIS) model in a genome context supports spatial representation of genome features at multiple scales with a versatile and expressive query capability beyond that supported by existing genome browsers. RESULTS: We implemented an interactive genome sequence feature map for the mouse genome in GenoSIS, an application that uses ArcGIS, a commercially available GIS software system. The genome features and their attributes are represented as spatial objects and data layers that can be toggled on and off according to user preferences or displayed selectively in response to user queries. GenoSIS supports the generation of custom genome maps in response to complex queries about genome features based on both their attributes and locations. Our example application of GenoSIS to the mouse genome demonstrates the powerful visualization and query capability of mature GIS technology applied in a novel domain. CONCLUSION: Mapping tools developed specifically for geographic data can be exploited to display, explore and interact with genome data. The approach we describe here is organism independent and is equally useful for linear and circular chromosomes. One of the unique capabilities of GenoSIS compared to existing genome browsers is the capacity to generate genome feature maps dynamically in response to complex attribute and spatial queries

A REGIONAL EXPERIMENT TO EVALUATE EFFECTS OF FIRE AND FIRE SURROGATE TREATMENTS IN THE SAGEBRUSH BIOME

SageSTEP is a comprehensive regional experiment that provides critical information to managers faced with a sagebrush steppe ecosystem that is increasingly at risk from wildfire, invasive plants, and climate change. The experiment provides managers with information that can be used to restore ecological communities across the 100+ million acres of the sagebrush biome. It is designed to match the temporal and spatial scales at which managers operate, is intended to reduce management risk and uncertainty of catastrophic wildfire to the greatest degree possible, and provides managers with information that allows them to better understand tradeoffs inherent in the choice of management alternatives. The project has several features that make it ideal for testing hypotheses from state‐andtransition theory, and for discovering information that can be directly applied in a management context ‐‐ it is long‐term, experimental, multisite, multivariate, and treatments are applied across condition gradients, allowing for potential identification of biotic thresholds. The project is designed to distinguish communities that have conditions that will allow them to recover on their own following fuel or restoration treatments, versus communities that have crossed biotic thresholds, and will therefore require more expensive active restoration. SageSTEP is designed as a long‐term study, such that measurements are planned for at least 10 years after treatment implementation, or through the 2018 field season. This final report therefore describes the short‐term effects of treatments, 2‐4 years after treatment implementation., or through the 2010 field season. The Joint Fire Science Program generously funded SageSTEP for its first six years, and this funding was crucial for building an infrastructure that has now set the stage for an unprecedented long‐term study that will provide badly needed information on sagebrush steppe restoration and fuel treatment effectiveness. The infrastructure we’ve built consists of the following eight features: 1. A network of 18 sites distributed across the Great Basin, Snake River Basin, and Columbia Basin, 11 sites in a replicated woodland experiment, and 7 sites in a replicated sage‐cheat experiment (Figure 1). Each site is equivalent to a statistical block consisting of an unmanipulated control, and a set of fire and fire surrogate treatments. 2. A network of weather and soil moisture stations distributed along with the sites, that provides information on inter‐annual and geographic variation in moisture and temperature, and that is being used to interpret patterns of ecological response. 3. A small by efficient staff, consisting of scientists and technicians, responsible for continued monitoring of ecological variables through time, and maintenance of the projects’ infrastructure. 4. A funding stream from several agency sources, with current resources adequate to run the project for at least three more years, and with agreements in place to fund the project through fiscal year 2015. 5. A web of partnerships among managers, scientists, students, stakeholders, and policymakers that has worked together to design the study, implement the treatments, and learn about how sagebrush steppe system respond to alternative restoration treatments. 6. A highly effective and influential outreach program, anchored by a popular website, designed to interpret and deliver scientific information collected by SageSTEP scientists, and to distribute other relevant information originating from outside the project. 7. An on‐line database, called the SageSTEP Data Store, that offers fully proofed and validated data to analysts working within SageSTEP, and which will eventually provide the same information to other interested users. 8. The Great Basin NEON Site, NSF’s atmospheric sampling station that will soon be built at the SageSTEP Onaqui site. This link with NSF provides SageSTEP with leverage for established additional vegetation and soil monitoring facilities at Onaqui. Over the past three years, since post‐treatment data collection commenced, SageSTEP has produced a considerable amount of information, most of it now published in a total of 32 scientific papers. Key outreach products include: ● Active web site (sagestep.org), anchoring a comprehensive outreach program ● User\u27s Guides for Western Juniper & Pinyon‐Juniper woodlands ● Two Fuel Guides, one each for pre‐treatment and post‐treatment conditions ● 15 quarterly newsletters ● Six manager workshops ● 11 tours or field trips ● Three national conference symposia, consisting of 24 papers (2 symposia planned) ● 57 contributed papers at conferences ● Seven Master’s Theses and two Ph.D. Dissertations ● 15 papers published in proceedings or reports ● Ten papers published in peer‐reviewed journals (17 papers currently in review

GeneWeaver: a web-based system for integrative functional genomics

High-throughput genome technologies have produced a wealth of data on the association of genes and gene products to biological functions. Investigators have discovered value in combining their experimental results with published genome-wide association studies, quantitative trait locus, microarray, RNA-sequencing and mutant phenotyping studies to identify gene-function associations across diverse experiments, species, conditions, behaviors or biological processes. These experimental results are typically derived from disparate data repositories, publication supplements or reconstructions from primary data stores. This leaves bench biologists with the complex and unscalable task of integrating data by identifying and gathering relevant studies, reanalyzing primary data, unifying gene identifiers and applying ad hoc computational analysis to the integrated set. The freely available GeneWeaver (http://www.GeneWeaver.org) powered by the Ontological Discovery Environment is a curated repository of genomic experimental results with an accompanying tool set for dynamic integration of these data sets, enabling users to interactively address questions about sets of biological functions and their relations to sets of genes. Thus, large numbers of independently published genomic results can be organized into new conceptual frameworks driven by the underlying, inferred biological relationships rather than a pre-existing semantic framework. An empirical ‘ontology’ is discovered from the aggregate of experimental knowledge around user-defined areas of biological inquiry

ProteomeScout: A repository and analysis resource for post-translational modifications and proteins

ProteomeScout (https://proteomescout.wustl.edu) is a resource for the study of proteins and their post-translational modifications (PTMs) consisting of a database of PTMs, a repository for experimental data, an analysis suite for PTM experiments, and a tool for visualizing the relationships between complex protein annotations. The PTM database is a compendium of public PTM data, coupled with user-uploaded experimental data. ProteomeScout provides analysis tools for experimental datasets, including summary views and subset selection, which can identify relationships within subsets of data by testing for statistically significant enrichment of protein annotations. Protein annotations are incorporated in the ProteomeScout database from external resources and include terms such as Gene Ontology annotations, domains, secondary structure and non-synonymous polymorphisms. These annotations are available in the database download, in the analysis tools and in the protein viewer. The protein viewer allows for the simultaneous visualization of annotations in an interactive web graphic, which can be exported in Scalable Vector Graphics (SVG) format. Finally, quantitative data measurements associated with public experiments are also easily viewable within protein records, allowing researchers to see how PTMs change across different contexts. ProteomeScout should prove useful for protein researchers and should benefit the proteomics community by providing a stable repository for PTM experiments

Global Landscape of a Co-Expressed Gene Network in Barley and its Application to Gene Discovery in Triticeae Crops

Accumulated transcriptome data can be used to investigate regulatory networks of genes involved in various biological systems. Co-expression analysis data sets generated from comprehensively collected transcriptome data sets now represent efficient resources that are capable of facilitating the discovery of genes with closely correlated expression patterns. In order to construct a co-expression network for barley, we analyzed 45 publicly available experimental series, which are composed of 1,347 sets of GeneChip data for barley. On the basis of a gene-to-gene weighted correlation coefficient, we constructed a global barley co-expression network and classified it into clusters of subnetwork modules. The resulting clusters are candidates for functional regulatory modules in the barley transcriptome. To annotate each of the modules, we performed comparative annotation using genes in Arabidopsis and Brachypodium distachyon. On the basis of a comparative analysis between barley and two model species, we investigated functional properties from the representative distributions of the gene ontology (GO) terms. Modules putatively involved in drought stress response and cellulose biogenesis have been identified. These modules are discussed to demonstrate the effectiveness of the co-expression analysis. Furthermore, we applied the data set of co-expressed genes coupled with comparative analysis in attempts to discover potentially Triticeae-specific network modules. These results demonstrate that analysis of the co-expression network of the barley transcriptome together with comparative analysis should promote the process of gene discovery in barley. Furthermore, the insights obtained should be transferable to investigations of Triticeae plants. The associated data set generated in this analysis is publicly accessible at http://coexpression.psc.riken.jp/barley/

The Genopolis Microarray Database

<p>Abstract</p> <p>Background</p> <p>Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood.</p> <p>Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions.</p> <p>Results</p> <p>The Genopolis Database system allows the community to build an object based MIAME compliant annotation of their experiments and to store images, raw and processed data from the Affymetrix GeneChip^®platform. It supports dynamical definition of controlled vocabularies and provides automated and supervised steps to control the coherence of data and annotations. It allows a precise control of the visibility of the database content to different sub groups in the community and facilitates exports of its content to public repositories. It provides an interactive users interface for data analysis: this allows users to visualize data matrices based on functional lists and sample characterization, and to navigate to other data matrices defined by similarity of expression values as well as functional characterizations of genes involved. A collaborative environment is also provided for the definition and sharing of functional annotation by users.</p> <p>Conclusion</p> <p>The Genopolis Database supports a community in building a common coherent knowledge base and analyse it. This fills a gap between a local database and a public repository, where the development of a common coherent annotation is important. In its current implementation, it provides a uniform coherently annotated dataset on dendritic cells and macrophage differentiation.</p

AgBase: supporting functional modeling in agricultural organisms

AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website