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1.  Phragmites australis management in the United States: 40 years of methods and outcomes 
AoB Plants  2014;6:plu001.
We reviewed all available studies on Phragmites australis management in the United States. Our results show that there is a heavy emphasis on herbicides to manage Phragmites, relative to other methods, and a lack of information on what types of plant communities establish once Phragmites is removed. Our model of Phragmites establishment and reproduction describes the invasion as a symptom of watershed-scale land use and disturbance. We advocate more holistic approaches to control and management that focus on improving water quality and minimizing human disturbance to deter future invasion and improve resilience of native plant communities.
Studies on invasive plant management are often short in duration and limited in the methods tested, and lack an adequate description of plant communities that replace the invader following removal. Here we present a comprehensive review of management studies on a single species, in an effort to elucidate future directions for research in invasive plant management. We reviewed the literature on Phragmites management in North America in an effort to synthesize our understanding of management efforts, identify gaps in knowledge and improve the efficacy of management. Additionally, we assessed recent ecological findings concerning Phragmites mechanisms of invasion and integrated these findings into our recommendations for more effective management. Our overall goal is to examine whether or not current management approaches can be improved and whether they promote reestablishment of native plant communities. We found: (i) little information on community-level recovery of vegetation following removal of Phragmites; and (ii) most management approaches focus on the removal of Phragmites from individual stands or groups of stands over a relatively small area. With a few exceptions, recovery studies did not monitor vegetation for substantial durations, thus limiting adequate evaluation of the recovery trajectory. We also found that none of the recovery studies were conducted in a landscape context, even though it is now well documented that land-use patterns on adjacent habitats influence the structure and function of wetlands, including the expansion of Phragmites. We suggest that Phragmites management needs to shift to watershed-scale efforts in coastal regions, or larger management units inland. In addition, management efforts should focus on restoring native plant communities, rather than simply eradicating Phragmites stands. Wetlands and watersheds should be prioritized to identify ecosystems that would benefit most from Phragmites management and those where the negative impact of management would be minimal.
doi:10.1093/aobpla/plu001
PMCID: PMC4038441  PMID: 24790122
Common reed; ecological restoration; herbicide; invasive plant; invasive species; management; Phragmites australis; watershed restoration.
2.  clearScience: Infrastructure for Communicating Data-Intensive Science 
Progress in biomedical research requires effective scientific communication to one’s peers and to the public. Current research routinely encompasses large datasets and complex analytic processes, and the constraints of traditional journal formats limit useful transmission of these elements. We are constructing a framework through which authors can not only provide the narrative of what was done, but the primary and derivative data, the source code, the compute environment, and web-accessible virtual machines. This infrastructure allows authors to “hand their machine”— prepopulated with libraries, data, and code—to those interested in reviewing or building off of their work. This project, “clearScience,” seeks to provide an integrated system that accommodates the ad hoc nature of discovery in the data-intensive sciences and seamless transitions from working to reporting. We demonstrate that rather than merely describing the science being reported, one can deliver the science itself.
PMCID: PMC3814454  PMID: 24303291
3.  SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments 
BMC Bioinformatics  2010;11:377.
Background
High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires.
Results
Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code.
Conclusion
The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services.
doi:10.1186/1471-2105-11-377
PMCID: PMC2916924  PMID: 20630057
4.  Adaptable data management for systems biology investigations 
BMC Bioinformatics  2009;10:79.
Background
Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage.
Results
The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents.
Conclusion
Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community.
doi:10.1186/1471-2105-10-79
PMCID: PMC2670281  PMID: 19265554
5.  Detailed transcriptome atlas of the pancreatic beta cell 
Background
Gene expression patterns provide a detailed view of cellular functions. Comparison of profiles in disease vs normal conditions provides insights into the processes underlying disease progression. However, availability and integration of public gene expression datasets remains a major challenge. The aim of the present study was to explore the transcriptome of pancreatic islets and, based on this information, to prepare a comprehensive and open access inventory of insulin-producing beta cell gene expression, the Beta Cell Gene Atlas (BCGA).
Methods
We performed Massively Parallel Signature Sequencing (MPSS) analysis of human pancreatic islet samples and microarray analyses of purified rat beta cells, alpha cells and INS-1 cells, and compared the information with available array data in the literature.
Results
MPSS analysis detected around 7600 mRNA transcripts, of which around a third were of low abundance. We identified 2000 and 1400 transcripts that are enriched/depleted in beta cells compared to alpha cells and INS-1 cells, respectively. Microarray analysis identified around 200 transcription factors that are differentially expressed in either beta or alpha cells. We reanalyzed publicly available gene expression data and integrated these results with the new data from this study to build the BCGA. The BCGA contains basal (untreated conditions) gene expression level estimates in beta cells as well as in different cell types in human, rat and mouse pancreas. Hierarchical clustering of expression profile estimates classify cell types based on species while beta cells were clustered together.
Conclusion
Our gene atlas is a valuable source for detailed information on the gene expression distribution in beta cells and pancreatic islets along with insulin producing cell lines. The BCGA tool, as well as the data and code used to generate the Atlas are available at the T1Dbase website (T1DBase.org).
doi:10.1186/1755-8794-2-3
PMCID: PMC2635377  PMID: 19146692
6.  T1DBase: integration and presentation of complex data for type 1 diabetes research 
Nucleic Acids Research  2006;35(Database issue):D742-D746.
T1DBase () [Smink et al. (2005) Nucleic Acids Res., 33, D544–D549; Burren et al. (2004) Hum. Genomics, 1, 98–109] is a public website and database that supports the type 1 diabetes (T1D) research community. T1DBase provides a consolidated T1D-oriented view of the complex data world that now confronts medical researchers and enables scientists to navigate from information they know to information that is new to them. Overview pages for genes and markers summarize information for these elements. The Gene Dossier summarizes information for a list of genes. GBrowse [Stein et al. (2002) Genome Res., 10, 1599–1610] displays genes and other features in their genomic context, and Cytoscape [Shannon et al. (2003) Genome Res., 13, 2498–2504] shows genes in the context of interacting proteins and genes. The Beta Cell Gene Atlas shows gene expression in β cells, islets, and related cell types and lines, and the Tissue Expression Viewer shows expression across other tissues. The Microarray Viewer shows expression from more than 20 array experiments. The Beta Cell Gene Expression Bank contains manually curated gene and pathway annotations for genes expressed in β cells. T1DMart is a query tool for markers and genotypes. PosterPages are ‘home pages’ about specific topics or datasets. The key challenge, now and in the future, is to provide powerful informatics capabilities to T1D scientists in a form they can use to enhance their research.
doi:10.1093/nar/gkl933
PMCID: PMC1781218  PMID: 17169983

Results 1-6 (6)