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http://datasharing.net

The U.S. National Institutes of Health Final NIH Statement on Sharing Research Data (NIH-OD-03-032) is now in effect. It specifies that all high-direct-cost NIH grant applications include plans for sharing of research data. To support and encourage collegial, enabling, and rewarding data sharing for neuroscience and beyond, the Laboratory of Neuroinformatics at Weill Medical College of Cornell University has established this site. A source of, and portal to, tools and proposals supporting the informed exchange of neuroscience data.

Proper citation: Datasharing.net (RRID:SCR_003312) Copy   

•   Source: SciCrunch Registry

http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:Jackal

Jackal is a collection of programs designed for the modeling and analysis of protein structures. Its core program is a versatile homology modeling package. It contains twelve individual programs, each with their own function.

Proper citation: Jackal (RRID:SCR_008665) Copy   

•   Source: SciCrunch Registry

http://pslid.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

Annotated database of fluorescence microscope images depicting subcellular location proteins with two interfaces: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. The annotations in PSLID provide a description of sample preparation and fluorescence microscope imaging.

Proper citation: Protein Subcellular Location Image Database (RRID:SCR_008663) Copy   

•   Source: SciCrunch Registry

http://iubio.bio.indiana.edu:8089/

Provides summary of gene and genomic information from eukaryotic organism databases. This includes gene symbol and full name, chromosome, genetic and molecular map information, Gene Ontology (Function/Location/Process) and gene homology, product information, links to extended gene information.

Proper citation: Eukaryote Genes (RRID:SCR_008617) Copy   

•   Source: SciCrunch Registry

http://www.datamonkey.org/

Web-based suite of phylogenetic analysis tools for use in evolutionary biology. Web application for comparative analysis of sequence alignments using statistical models. Used for analyzing evolutionary signatures in sequence data. Datamonkey 2.0 provides curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application.

Proper citation: Datamonkey (RRID:SCR_010278) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/InterNano

A custom-built terminology to describe the nanomanufacturing enterprise.

Proper citation: InterNano Nanomanufacturing Taxonomy (RRID:SCR_010346) Copy   

•   Source: SciCrunch Registry

http://www.aoncadis.org

A repository and data management services for Arctic research data. Data include long-term observational timeseries, local, regional, and system-scale research from many diverse domains.

Proper citation: ACADIS Gateway (RRID:SCR_010473) Copy   

•   Source: SciCrunch Registry

http://organelledb.lsi.umich.edu/

Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.

Proper citation: Organelle DB (RRID:SCR_007837) Copy   

•   Source: SciCrunch Registry

http://www.fgsc.net/

The Fungal Genetics Stock Center is a resource available to the Fungal Genetics research community and to educational and research organizations in general. While some fungi can cause disease in humans, most people have innate immunity against fungi. Some people with diseases of the immune system are at increased risk of infection by fungi. Drugs have been developed in the last 5 years that help with this. Fungal Genetics is the study of genes and genetic traits in fungi. In the past this has been important in the elucidation of what a gene is, what the genetic material is, how genes relate to enzymes, how enzymes relate to traits and how important traits change or evolve. In the present, Fungal Genetics is important to understanding how fungi are pathogens of plants and animals, how fungi can be used in industry for the production of enzymes, chemicals, food, and drugs. Fungi are also essential to processing bio-mass in the attempt to use ethanol as a fuel source. The FGSC is funded largely by a grant from the National Science Foundation (Award Number 0235887) of the United States of America. Sponsors: Supported by a grant from the National Science Foundation.

Proper citation: Fungal Genetics Stock Center (RRID:SCR_008143) Copy   

•   Source: SciCrunch Registry

http://www.poissonboltzmann.org/apbs/

APBS is a software package for modeling biomolecular solvation through solution of the Poisson-Boltzmann equation (PBE), one of the most popular continuum models for describing electrostatic interactions between molecular solutes in salty, aqueous media. APBS was designed to efficiently evaluate electrostatic properties for such simulations for a wide range of length scales to enable the investigation of molecules with tens to millions of atoms. It also provides implicit solvent models of nonpolar solvation which accurately account for both repulsive and attractive solute-solvent interactions. APBS uses FEtk (the Finite Element ToolKit) to solve the Poisson-Boltzmann equation numerically. FEtk is a portable collection of finite element modeling class libraries written in an object-oriented version of C. It is designed to solve general coupled systems of nonlinear partial differential equations using adaptive finite element methods, inexact Newton methods, and algebraic multilevel methods.

Proper citation: Adaptive Poisson-Boltzmann Solver (RRID:SCR_008387) Copy   

•   Source: SciCrunch Registry

http://opm.phar.umich.edu/

Database that provides a collection of transmembrane, monotopic and peripheral proteins from the Protein Data Bank whose spatial arrangements in the lipid bilayer have been calculated theoretically and compared with experimental data. The database allows analysis, sorting and searching of membrane proteins based on their structural classification, species, destination membrane, numbers of transmembrane segments and subunits, numbers of secondary structures and the calculated hydrophobic thickness or tilt angle with respect to the bilayer normal.

Proper citation: Orientations of Proteins in Membranes database (RRID:SCR_011961) Copy   

•   Source: SciCrunch Registry

http://www.internano.org/

Database and knowledge base of techniques for processing nanoscale materials, devices, and structures that includes step-by-step descriptions, images, notes on methodology and environmental variables, and associated references and patent information. The purpose of the Process Database is to facilitate the sharing of appropriate process knowledge across laboratories.The processes included here have been previously published or patented

Proper citation: InterNano Process Database (RRID:SCR_013719) Copy   

•   Source: SciCrunch Registry

http://wings-workflows.org

A software application which assists scientists with designing computational experiments. WINGS is a semantic workflow system which incorporates semantic constraints about datasets and workflow components into its workflow representations. The workflow system has an open modular design and can be easily integrated with other existing workflow systems and execution frameworks to extend them with semantic reasoning capabilities. WINGS also allows users to express high-level descriptions of their analysis goals, and assists them by automatically and systematically generating possible workflows that are consistent with that request. In cases where privacy or off-line use are important, WINGS can submit workflows in a scripted format for execution in the local host. It uses Pegasus or OODT as the execution engine for large-scale distributed workflow execution.

Proper citation: WINGS (RRID:SCR_013997) Copy   

•   Source: SciCrunch Registry

http://animatlab.com/

A software tool that combines biomechanical simulation and biologically realistic neural networks to create realistic models of, and perform tests on, biomechanical workings. AnimatLab was primarily designed to model and test the operation of neural circuits that might produce behavior patterns observed in an intact animal. Users can create an animalistic or robotic body and place it in a virtual environment with physics that are accurate and realistic. Users can then design a nervous system that controls the behavior of the body within the physically realistic environment. Various models for different types of actions, builds, and movements are available.

Proper citation: AnimatLab (RRID:SCR_014252) Copy   

•   Source: SciCrunch Registry

http://neurodata.io/

Project portal dedicated to understand animal and machine intelligence and repository of data and tools. Suite of tools to analyze and graph imaging data. Image and data repository for large, publicly available neuro-specific data files and images. Contains tools for analytics, databases, cloud computing, and Web-services applied to both big neuroimages and big neurographs.

Proper citation: neurodata (RRID:SCR_014264) 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