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The Oomycete Molecular Genetics Research Collaboration Network (OMGN) is a network for research collaboration for investigators interested in oomycete molecular genetics and genomics. The goals of the OMGN is to facilitate the integration of these investigators into the community and to further strengthen the cooperative culture of this community. A particular emphasis is placed on training and integrating junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. Because of their economic impact as plant pathogens, molecular, genetic and genomics studies are well advanced in many oomycete species. These organisms have served as lead species for the entire Stramenopiles lineage, a major radiation of crown eukaryotes, distinct from plants, animals and fungi. The oomycete molecular genetics community has a strong culture of collaboration and communication, and sharing of techniques and resources. With the recent blossoming of genetic and genomic tools for oomycetes, many new investigators, from a variety of backgrounds, have become interested in oomycete molecular genetics and genomics. The proposed network is open to all researchers with an interest in oomycete molecular genetics and genomics, either at an experimental or a computational level. Investigators new to the field are always welcome, especially those interested in saprophytes and animal pathogens. Goals of OMGN # Provide training to o��mycete molecular genetics researchers, especially those from smaller institutions, in the use of bioinformatics and genomics resources. # Promote the entry, participation and training of new investigators into the field of o��mycete genomics, particularly junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. # Promote communication and collaboration, and minimize duplication of effort, within the worldwide o��mycete genomics community. # Support an O��mycete Genomics Resources Center to maintain and distribute training and research materials produced by community genomics projects. The network''s activities have been supported by two grants from the NSF Research Collaboration Networks in Biology program.
Proper citation: OMGN (RRID:SCR_005781) Copy
http://mcbc.usm.edu/gofetcher/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool
Proper citation: GOfetcher (RRID:SCR_005681) Copy
A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications.
Proper citation: Viking Viewer for Connectomics (RRID:SCR_005986) Copy
A social visualization repository for the scientific workflow management system VisTrails providing a platform for sharing and executing computational tasks. It adopts the model used by social Web sites and that integrates a set of usable tools and a scalable infrastructure to provide an environment for scientists to collaboratively analyze and visualize data. crowdLabs aims to foster collaboration but was specifically designed to support the needs of computational scientists, including the ability to access high-performance computers and manipulate large volumes of data. By providing mechanisms that simplify the publishing and use of analysis pipelines, it allows IT personnel and end users to collaboratively construct and refine portals. This lowers the barriers for the use of scientific analyses and enables broader audiences to contribute insights to the scientific exploration process, without the high costs incurred by traditional portals. In addition, it supports a more dynamic environment where new exploratory analyses can be added on-the-fly.
Proper citation: crowdLabs (RRID:SCR_006294) Copy
http://evolution.genetics.washington.edu/phylip.html
A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems.
Proper citation: PHYLIP (RRID:SCR_006244) Copy
A project that observes the processes of adaptive evolution in nature, and tests evolutionary hypotheses, by studying populations of guppies on the Caribbean island of Trinidad. Darwin thought that evolution by natural selection occurred very slowly, over hundreds if not thousands of years. Evolutionary biologists now know that evolutionary changes in species can happen very quickly, over a relatively few generations. The National Science Foundation (NSF), through its Integrative Biological Research (FIBR) program, is funding a 5-year study by 13 biologists from colleges, universities, and research institutions throughout the United States and Canada, to study the relationship of adaptive evolution and environmental circumstances. The Trinidadian guppy (Poecilia reticulata) is an excellent species for these purposes because: * It matures rapidly (one generation = 3-4 months) * It inhabits different ecological environments that can be easily manipulated On Trinidad, guppies live in streams, or portions of streams, that can differ in the species of predators that the guppies have to contend with. Some streams are high-predation environments, others low-predation. Different predation environments are often right next to one another, separated by a waterfall (which neither guppies nor predators can cross). Guppies from high-predation environments experience much higher mortality rates than do guppies in low-predation environments. High mortality is associated with the following characteristics, all of which have a genetic basis: * Earlier maturity * Greater investment of resources in reproduction * More and smaller offspring. We have found that mortality rates can be manipulated by: * Transplanting guppies from high-predation localities into sites from which they and their predators had previously been excluded by natural waterfalls, thus lowering mortality rates; * Introducing predators into low-predation sites, thus increasing mortality rates. Such experiments have shown that species evolve as predicted by theory. We have also found that evolution by natural selection can be remarkably fast, on the order of four to seven orders of magnitude faster than had been inferred from the fossil record.
Proper citation: Guppy Project (RRID:SCR_006255) Copy
Open access knowledge base for microbial natural products discovery. Database of microbially derived natural product structures. Provides coverage of bacterial and fungal natural products to visualize chemical diversity. Includes compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. Interactive web portal permits searching by structure, substructure, and physical properties. Provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. Atlas has been developed under FAIR principles.
Proper citation: Natural Products Atlas (RRID:SCR_025107) Copy
Publicly accessible 3D data repository where subject experts, educators, and general public can find, view, interact with, and download 3D and 2D media representing physical objects important to the world’s natural history, cultural heritage, and scientific collections. Media data are contributed by a community that includes museums, institutions, researchers, scholars, and other subject experts who use MorphoSource to archive data, share findings, and increase scholarly impact. Contributed media represent both biological objects such as fossils and representatives of living species, as well as artifacts and objects created by humans that are critical to our shared cultural heritage.
Proper citation: MorphoSource (RRID:SCR_025654) Copy
https://github.com/zhouhj1994/LinDA
Software linear models for differential abundance analysis of microbiome compositional data. Used to tackle compositional effects in differential abundance analysis. It fits linear regression models on centered log2-ratio transformed data, identifies bias term due to transformation and compositional effect, and corrects bias using mode of regression coefficients. It could fit mixed-effect models.
Proper citation: LinDA (RRID:SCR_025966) Copy
http://www.scienceexchange.com/facilities/nnin-nano-research-facility-wustl
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 15,2024. Nano Research Facility (NRF) at Washington University in St. Louis is a NNIN nodal facility supported by the National Science Foundation. It cultivates an open, shared research, and education environment that brings researchers across disciplines together, particularly in the emerging area of nanomaterials with applications in the energy, environment, and biomedical fields. The mission is to be a resource to the scientific and technical community for the advancement of nanoscience and nanotechnology in a safe and environmentally benign manner. NRF includes a micro- and nano-fabrication lab (clean room), surface characterization lab, particle technology lab, and imaging lab with a focus on bio-imaging. NRF provides unique technical expertise in: Knowledge-based synthesis of nanostructured materials Particle instrumentation tools for toxicity studies Non-invasive imaging modalities for biological applications Clean Energy Applications Energy and Environmental nanotechology Environmental Health and Safety As a member of the National Nanotechnology Infrastructure Network (NNIN), supported by the National Science Foundation, NRF is available to both academic and industrial users nation-wide and across the globe.
Proper citation: WUSTL NNIN - Nano Research Facility (RRID:SCR_012674) Copy
Provides genomics and molecular biology services for University of Delaware research groups and outside users.Supports genomic research through established expertise with genomics technologies.
Proper citation: University of Delaware Sequencing and Genotyping Center Core Facility (RRID:SCR_012230) Copy
http://www.scienceexchange.com/facilities/genomics-core-facility-brown
Provides genomics and proteomics equipment to researchers at Brown University and to entire Rhode Island research community, as well as assistance with experimental design, trouble shooting, and data analysis. Offers Affymetrix microarray and Illumina NextGeneration services to academic community and external customers.
Proper citation: Brown University Genomics Core Facility (RRID:SCR_012217) Copy
https://github.com/kharchenkolab/conos
Software R package for joint analysis of multiple single-cell RNA-seq datasets. Used to wire together large collections of single-cell RNA-seq datasets, which allows for both identification of recurrent cell clusters and propagation of information between datasets in multi-sample or atlas-scale collections.
Proper citation: Conos (RRID:SCR_026381) Copy
https://github.com/compgenomics/MeTPeak
Software package for finding the location of m6A sites in MeRIP-seq data.
Proper citation: MeTPeak (RRID:SCR_026533) Copy
https://github.com/YuningHao/FARDEEP
Software R tool for enumerating immune cell subsets from whole tumor tissue samples. Utilizes adaptive least trimmed square to automatically detect and remove outliers before estimating cell compositions.
Proper citation: FARDEEP (RRID:SCR_026704) Copy
https://github.com/DerrickWood/kraken2
Software tool as second version of Kraken taxonomic sequence classification system.
Proper citation: kraken2 (RRID:SCR_026838) Copy
https://github.com/KrishnaswamyLab/PHATE
Software tool for visualizing high dimensional data using novel conceptual framework for learning and visualizing manifold to preserve both local and global distances.
Proper citation: PHATE (RRID:SCR_027119) Copy
https://nationalmaglab.org/user-facilities/high-b-t-facility
Facility to conduct experiments in high magnetic fields up to 15 tesla and at very low temperatures down to 0.4 mK simultaneously. Located at University of Florida in Gainesville, it is operated as part of Physics Department Microkelvin Laboratory.
Proper citation: National High Magnetic Field Laboratory High B/T Core Facility (RRID:SCR_017360) Copy
Facility offers array of solid state, solution state, MRI/S (animal and human), MR microscopy and diffusion capabilities and techniques. Among their machines is 900 MHz 105 mm bore magnet. Techniques and instruments are available at two different MagLab facilities in Florida, NMR-MRI/S Facility at MagLab headquarters near Florida State University in Tallahassee and Advanced Magnetic Resonance Imaging and Spectroscopy Facility (AMRIS) housed within McKnight Brain Institute at University of Florida in Gainesville.
Proper citation: National High Magnetic Field Laboratory Advanced Magnetic Resonance Imaging and Spectroscopy Core Facility (RRID:SCR_017362) Copy
http://crl.berkeley.edu/molecular-imaging-center/
Microscopy core specializing in laser based fluorescence techniques. Offers training and expertise in 20 different microscope systems, including live cell and in vivo imaging, laser scanning (LSM) and spinning disk (SDC) confocal, multi-photon (2p), fluorescent lifetime imaging (FLIM), light-sheet microscopy (SPIM), super resolution (Airyscan), slide scanning and patterned illumination for optogenetic manipulation and readout. Provides offline computer analysis workstations for image processing, visualization and analysis, including GPU workstations. MIC operates in 3 different buildings on campus, with primary locations in Life Sciences Addition (LSA), North-side core in Barker Hall, and small outpost in Li Ka Shing Center for Biomedical and Health Sciences (LKS).Provides equipment in categories:Confocal and multi photon laser scanning microscopes,Spinning disk confocal microscopes,Lightsheet (SPIM) microscopes,Epifluorescence/widefield scopes and Computer workstations.
Proper citation: University of California at Berkeley Cancer Research Laboratory Molecular Imaging Center Core Facility (RRID:SCR_017852) Copy
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