Tools   Select Another Resource Report Type

http://nbc.ece.drexel.edu/

Webserver for taxonomic classification of metagenomic reads.

Proper citation: NBC (RRID:SCR_004772) Copy   

•   Source: SciCrunch Registry

http://gila.bioengr.uic.edu/snp/toposnp

A topographic database for analyzing non-synonymous SNPs (nsSNPs) that can be mapped onto known 3D structures of proteins. These include disease- associated nsSNPs derived from the Online Mendelian Inheritance in Man (OMIM) database and other nsSNPs derived from dbSNP, a resource at the National Center for Biotechnology Information that catalogs SNPs. TopoSNP further classifies each nsSNP site into three categories based on their geometric location: those located in a surface pocket or an interior void of the protein, those on a convex region or a shallow depressed region, and those that are completely buried in the interior of the protein structure. These unique geometric descriptions provide more detailed mapping of nsSNPs to protein structures. It also includes relative entropy of SNPs calculated from multiple sequence alignment as obtained from the Pfam database (a database of protein families and conserved protein motifs) as well as manually adjusted multiple alignments obtained from ClustalW. These structural and conservational data can be useful for studying whether nsSNPs in coding regions are likely to lead to phenotypic changes. TopoSNP includes an interactive structural visualization web interface, as well as downloadable batch data.

Proper citation: TopoSNP (RRID:SCR_005572) Copy   

•   Source: SciCrunch Registry

https://tree.opentreeoflife.org/opentree/argus/opentree14.9@ott93302

Project aims to construct comprehensive, dynamic and digitally available tree of life by synthesizing published phylogenetic trees along with taxonomic data.

Proper citation: Open Tree of Life (RRID:SCR_024603) Copy   

•   Source: SciCrunch Registry

https://masst.gnps2.org/microbemasst/

Web taxonomically informed mass spectrometry search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging database of over 60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns.

Proper citation: microbeMASST (RRID:SCR_024713) Copy   

•   Source: SciCrunch Registry

https://brains.anatomy.msu.edu/brains/sheep/index.html

Online portal and image database of coronal sections of the sheep brain. Each image contains stained sections of cell bodies and myelinated fibers; nuclei and tracts are labeled.

Proper citation: Sheep Brain Atlas (RRID:SCR_001752) Copy   

•   Source: SciCrunch Registry

http://workspace.earthcube.org/cinergi

A project constructing a community inventory and knowledge base on geoscience information resources to meet the challenge of finding resources across disciplines, assessing their fitness for use in specific research scenarios, and providing tools for integrating and re-using data from multiple domains. The project team envisions a comprehensive system linking geoscience resources, users, publications, usage information, and cyberinfrastructure components. This system would serve geoscientists across all domains to efficiently use existing and emerging resources for productive and transformative research.

Proper citation: CINERGI (RRID:SCR_002188) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/frats/

Software for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.

Proper citation: Functional Regression Analysis of DTI Tract Statistics (RRID:SCR_002293) Copy   

•   Source: SciCrunch Registry

http://geodynamics.org/

Community-driven organization that develops and disseminates software for geophysics and related fields. They host codes in a wide range of disciplines in geodynamics and computational science including geodynamo, long-term tectonics, magma migration, mantle dynamics, seismology, and short-term crustal dynamics.

Proper citation: Computational Infrastructure for Geodynamics (RRID:SCR_003371) Copy   

•   Source: SciCrunch Registry

http://research.amnh.org/atol/files/

Project whose aim is to produce a robust phylogeny of all the deepest branches within a mega-diverse group, the spiders, by combining a massive amount of newly generated comparative genomic data with a substantial set of new and re-assessed data on morphology and behavior. They propose to collect a huge amount of genomic information in order to test and improve the results achieved by over 50 detailed morphological cladistic analyses conducted by more than 30 investigators during the past 15 years. The insignificant amount of genomic work to date on spiders has been uncoordinated and of little utility for broad-scale phylogenetic investigation. The advent of high-throughput DNA sequencing, however, makes it feasible to examine substantial parts of the genome across a dense sampling of spider taxa. They propose to sequence at least 50 loci (genome samples of 500-1,000 or more base pairs that can be sequenced as single pieces in both directions simultaneously) for representatives of at least 500 genera of spiders and their closest relatives (the whipscorpion orders Amblypygi, Uropygi, and Schizomida). These genera will be carefully selected by a sampling strategy designed to maximize the resolution of deep branches within spider phylogeny, and will purposefully include all the previously most-favored study organisms of ethologists, ecologists, physiologists, and developmental and molecular biologists, thus integrating and contextualizing their research. Data matrices will be produced that combine the new genomic data with a new, comprehensive survey of morphological and behavioral homologies, offering a unique index to all comparative data on one large group. New computer software, designed in large part by members of their group and using massively parallel processing to achieve supercomputing capability, makes such analyses feasible.

Proper citation: Tree of Life: Phylogeny of Spiders (RRID:SCR_003801) Copy   

•   Source: SciCrunch Registry

https://www.opensciencedatacloud.org/

Service that provides petabyte-scale cloud resources to analyze, manage, and share scientific data. It is designed to serve medium to large sized research projects by managing and operating a secure cloud computing infrastructure that can be shared across a project. This Science as a Service approach to research saves scientists and their funders valuable time and money. All of the software developed is open source and hosted on GitHub. The OSDC also has 1PB of public data in a wide variety of disciplines. The data sets can downloaded over the internet or high performance networks such as Internet2, as well as computed over directly on the OSDC.

Proper citation: Open Science Data Cloud (RRID:SCR_003523) Copy   

•   Source: SciCrunch Registry

http://www.sb.cs.cmu.edu/drem

The Dynamic Regulatory Events Miner (DREM) allows one to model, analyze, and visualize transcriptional gene regulation dynamics. The method of DREM takes as input time series gene expression data and static transcription factor-gene interaction data (e.g. ChIP-chip data), and produces as output a dynamic regulatory map. The dynamic regulatory map highlights major bifurcation events in the time series expression data and transcription factors potentially responsible for them. DREM 2.0 was released and supports a number of new features including: * new static binding data for mouse, human, D. melanogaster, A. thaliana * a new and more flexible implementation of the IOHMM supports dynamic binding data for each time point or as a mix of static/dynamic TF input * expression levels of TFs can be used to improve the models learned by DREM * the motif finder DECOD can be used in conjuction with DREM and help find DNA motifs for unannotated splits * new features for the visualization of expressed TFs, dragging boxes in the model view, and switching between representations

Proper citation: Dynamic Regulatory Events Miner (RRID:SCR_003080) Copy   

•   Source: SciCrunch Registry

http://impactstory.org/

A web application which provides altmetrics to help researchers measure and share the impacts of their research outputs. After making a profile, scientists can track which of their publications are most popular through number of citations, frequency of PDF downloads, etc. Information from research outputs such as journal articles, blog posts, datasets, and software contribute to a user's impact, which is viewable in their profile.

Proper citation: ImpactStory (RRID:SCR_002632) Copy   

•   Source: SciCrunch Registry

http://phenoscape.org/

Project to create a scalable infrastructure that enables linking phenotypes across different fields of biology by the semantic similarity of their descriptions.

Proper citation: Phenoscape (RRID:SCR_003799) Copy   

•   Source: SciCrunch Registry

http://www.icn.ucl.ac.uk/motorcontrol/imaging/propatlas.htm

A probabilistic atlas of the cerebellar lobules in the space defined by the MNI152 template. The anatomical definitions are based on the fMRI atlas of an individual cerebellum by Schmahmann et al. (2000). To obtain a representative anatomical atlas, we separately masked the lobules on T1-weighted MRI scans (1mm isotropic resolution) of 20 healthy young participants (10 male, 10 female, average age 23.7 yrs). Using a different set of 23 participants, we also masked the deep cerebellar nucelei. These cerebella were then aligned using different commonly used normalization algorithms. The resultant probabilistic maps allow for the valid assignment of functional activations to specific cerebellar lobules and the nuclei, while providing a quantitative measure of the certainty of such assignments. Furthermore, maximum probability maps derived from these atlases can be used to define regions of interest (ROIs) in functional neuroimaging and neuroanatomical research. The atlas is included in the newer releases of FSL and the Anatomy toolbox. More version of the atlases for use with MRICroN are also available.

Proper citation: Probabilistic atlas of the human cerebellum (RRID:SCR_008797) Copy   

•   Source: SciCrunch Registry

http://www.plantgdb.org/

Software tools and databases for plant genomics.

Proper citation: PlantGDB (RRID:SCR_013166) Copy   

•   Source: SciCrunch Registry

http://arf.fsu.edu/

National repository for geological materials collected in polar regions housing over 20,000 meters of deep-sea core sediment and over 5,000 kg of dredge, trawl, and grab samples, the largest such Southern Ocean collection in the world. These materials have been acquired from over 90 USAP research vessel cruises. The Facility also houses and curates nearly 3,000 meters of rotary cored geological material acquired by NSF supported drilling programs in the Antarctic. Replacement cost of this core inventory in terms of ship and ice-based drilling is conservatively estimated to be in the range of $150 to $200M. SESAR or the the System for Earth Sample Registration is a service provided by the IDEA. SESAR operates the registry that distributes the International Geo Sample Number IGSN. SESAR catalogs and preserves sample metadata profiles, and provides access to the sample catalog via the Global Sample Search. Facility services include:
* curation of the existing collections at the facility
* onsite ship and land based curatorial services
* receipt and processing of new cores
* core description and publication of core descriptions
* distribution of samples from the collection to authorized scientists
* hosting of scientific meetings and workshops
* tours, lectures, and student education and training in Antarctic geoscience
* maintenance of:
** a core and sample database
** an Antarctic geology and marine geology reference library and a searchable End Note computer database of the entire collection
** a satellite IODP/MRC for nannofossils and diatoms

Proper citation: Antarctic Marine Geology Research Facility (RRID:SCR_002213) Copy   

•   Source: SciCrunch Registry

http://www.cise.ufl.edu/~tichen/ShapeComplexAtlas.zip

A Matlab demo for constructing a neuro-anatomical shape complex atlas from 3D MRI brain structures, based on the paper Ting Chen, Anand Rangarajan, Stephan J. Eisenschenk and Baba C. Vemuri, Construction of a Neuroanatomical Shape Complex Atlas from 3D MRI Brain Structures. In NeuroImage, Volume 60, Page 1778-1787, 2012

Proper citation: ShapeComplexAtlas (RRID:SCR_002553) Copy   

•   Source: SciCrunch Registry

http://total-impact.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 8, 2017. Service that aggregates altmetrics: diverse impacts from articles, datasets, blog posts, and more, to create a measure of the impact of scholarly output. * view metrics: Point to research products in Slideshare, GitHub, and Dryad. Import items from Google Scholar profiles or a BibTex file and the output is a metrics report that can be viewed and shared. * embed anywhere: Use the full-featured API to add metrics to projects. Or drop the embeddable Javascript widget into a publishing platform''s HTML. * Free - metrics data (and source code). They believe open altmetrics are key for building the coming era of Web-native science.

Proper citation: total impact.org (RRID:SCR_005952) Copy   

•   Source: SciCrunch Registry

http://clovr.org/

A desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing.

Proper citation: CloVR (RRID:SCR_005290) Copy   

•   Source: SciCrunch Registry

http://www.pymvpa.org

A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.

Proper citation: PyMVPA (RRID:SCR_006099) Copy   

•   Source: SciCrunch Registry