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http://smallrna.udel.edu/index.php

This project has developed a sequence dataset of plant small RNAs based on the hypothesis that most if not all plants utilize important small RNA signaling networks. Different plant families are likely to have both common and lineage-specific miRNAs or other small RNAs with important biological roles. Comparative genomics approaches can be applied to distinguish potential miRNAs from siRNAs and to match the miRNAs to the target sequences. This project develops an unparalleled resource of millions of plant small RNAs for comparative analyses. The project includes sequencing of small RNAs from a diverse and agronomically-relevant set of plant species, focused analyses of important members of the Solanaceae and Poaceae, and development of a small RNA database and web interface for public access and analysis of data. These data will allow the experimental characterization of the majority of biologically important small RNAs for a range of plant species, and will be tremendously useful to a broad set of plant biologists interested in development, stress responses, epigenetics, evolution, RNA biology and other traits impacted by small RNAs. We offer a variety of tools to query the small RNA data set, with options to identify sequences based on homology, expression levels, conservation, or potential function: 1. Small RNA mapping tool: searches for small RNAs perfectly matching a genomic sequence provided by the user. 2. Small RNA mismatch tool: searches the database for small RNAs or other short sequences provided by the user, allowing mismatches. 3. Library-comparison tool to identify conserved small RNAs. 4. Library-comparison tool to identify differentially regulated small RNAs. 5. Reverse Target Prediction.

Proper citation: Comparative Sequencing of Plant Small RNAs (RRID:SCR_007003) Copy   

•   Source: SciCrunch Registry

http://hendrix.imm.dtu.dk/software/lyngby/

Matlab toolbox for the analysis of functional neuroimages (PET, fMRI). The toolbox contains a number of models: FIR-filter, Lange-Zeger, K-means clustering among others, visualizations and reading of neuroimaging files.

Proper citation: Lyngby (RRID:SCR_007143) Copy   

•   Source: SciCrunch Registry

http://earthref.org/MAGIC/

Databases that accept and provide access to paleomagnetic and rock magnetic data. The paleomagnetic data range from individual measurements to specimen, sample or site level results, including a wide variety of derived parameters or associated rock magnetic measurements. The rock magnetic database includes data collected during rock magnetic experiments on remanence, anisotropy, hysteresis and susceptibility. The MagIC Console Software provides an effective environment in Microsoft Excel where users can collate and prepare their paleomagentic and rock magnetic data for uploading in the Online MagIC Database.

Proper citation: Magnetics Information Consortium (RRID:SCR_007098) Copy   

•   Source: SciCrunch Registry

http://www.genes2cognition.org/

A neuroscience research program that studies genes, the brain and behavior in an integrated manner, established to elucidate the molecular mechanisms of learning and memory, and shed light on the pathogenesis of disorders of cognition. Central to G2C investigations is the NMDA receptor complex (NRC/MASC), that is found at the synapses in the central nervous system which constitute the functional connections between neurons. Changes in the receptor and associated components are thought to be in a large part responsible for the phenomenon of synaptic plasticity, that may underlie learning and memory. G2C is addressing the function of synapse proteins using large scale approaches combining genomics, proteomics and genetic methods with electrophysiological and behavioral studies. This is incorporated with computational models of the organization of molecular networks at the synapse. These combined approaches provide a powerful and unique opportunity to understand the mechanisms of disease genes in behavior and brain pathology as well as provide fundamental insights into the complexity of the human brain. Additionally, Genes to Cognition makes available its biological resources, including gene-targeting vectors, ES cell lines, antibodies, and transgenic mice, generated for its phenotyping pipeline. The resources are freely-available to interested researchers.

Proper citation: Genes to Cognition: Neuroscience Research Programme (RRID:SCR_007121) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/fmridatacenter/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 25, 2013 Public curated repository of peer reviewed fMRI studies and their underlying data. This Web-accessible database has data mining capabilities and the means to deliver requested data to the user (via Web, CD, or digital tape). Datasets available: 107 NOTE: The fMRIDC is down temporarily while it moves to a new home at UCLA. Check back again in late Jan 2013! The goal of the Center is to help speed the progress and the understanding of cognitive processes and the neural substrates that underlie them by: * Providing a publicly accessible repository of peer-reviewed fMRI studies. * Providing all data necessary to interpret, analyze, and replicate these fMRI studies. * Provide training for both the academic and professional communities. The Center will accept data from those researchers who are publishing fMRI imaging articles in peer-reviewed journals. The goal is to serve the entire fMRI community.

Proper citation: fMRI Data Center (RRID:SCR_007278) Copy   

•   Source: SciCrunch Registry

http://nsr.bioeng.washington.edu/

Database of physiological, pharmacological, and pathological information on humans and other organisms and integration through computational modeling. Models include everything from diagrammatic schema, suggesting relationships among elements composing a system, to fully quantitative, computational models describing the behavior of physiological systems and an organism''s response to environmental change. Each mathematical model is an internally self-consistent summary of available information, and thereby defines a working hypothesis about how a system operates. Predictions from such models are subject to test, with new results leading to new models.BR /> A Tool developed for the NSR Physiome project is JSim, an open source, free software. JSim is a Java-based simulation system for building quantitative numeric models and analyzing them with respect to experimental reference data. JSim''s primary focus is in physiology and biomedicine, however its computational engine is quite general and applicable to a wide range of scientific domains. JSim models may intermix ODEs, PDEs, implicit equations, integrals, summations, discrete events and procedural code as appropriate. JSim''s model compiler can automatically insert conversion factors for compatible physical units as well as detect and reject unit unbalanced equations. JSim also imports the SBML and CellML model archival formats. All JSim models are open source. Goals of the Physiome Project: - To develop and database observations of physiological phenomenon and interpret these in terms of mechanism (a fundamentally reductionist goal). - To integrate experimental information into quantitative descriptions of the functioning of humans and other organisms (modern integrative biology glued together via modeling). - To disseminate experimental data and integrative models for teaching and research. - To foster collaboration amongst investigators worldwide, to speed up the discovery of how biological systems work. - To determine the most effective targets (molecules or systems) for therapy, either pharmaceutic or genomic. - To provide information for the design of tissue-engineered, biocompatible implants.

Proper citation: NSR Physiome Project (RRID:SCR_007379) Copy   

•   Source: SciCrunch Registry

https://dataverse.org/

Project portal for publishing, citing, sharing and discovering research data. Software, protocols, and community connections for creating research data repositories that automate professional archival practices, guarantee long term preservation, and enable researchers to share, retain control of, and receive web visibility and formal academic citations for their data contributions. Researchers, data authors, publishers, data distributors, and affiliated institutions all receive appropriate credit. Hosts multiple dataverses. Each dataverse contains studies or collections of studies, and each study contains cataloging information that describes the data plus the actual data files and complementary files. Data related to social sciences, health, medicine, humanities or other sciences with an emphasis in human behavior are uploaded to the IQSS Dataverse Network (Harvard). You can create your own dataverse for free and start adding studies for your data files and complementary material (documents, software, etc). You may install your own Dataverse Network for your University or organization.

Proper citation: Dataverse Network Project (RRID:SCR_001997) Copy   

•   Source: SciCrunch Registry

https://ncma.bigelow.org/

National marine phytoplankton collection, maintaining over 2700 strains from around the world, most are marine phytoplankton but they also have benthic, macrophytic, freshwater and heterotrophic organisms - now incorporating bacteria and viruses. Strain records have (when available): * collection and isolation information * culturing medium recipes and growth conditions * photographs * GenBank accession link * collection site map * link to the taxonomic database Micro*scope The deposition of new strains are welcome if the strains are a valuable addition to the collection. Examples include strains that are referred to in publications, contain interesting molecular, biochemical or physiological properties, are the basis for taxonomic descriptions, are important for aquaculture, or are from an unusual geographical location or ecological habitat. The NCMA offers a course in phytoplankton culturing techniques and facilities for visiting scientists are available at the new laboratories in East Boothbay, Maine. Services include: Mass Culturing DNA and RNA, Purification, Private Holdings, Culture Techniques Course, Visiting Scientists, Single Cell Genomics, Flow Cytometry, Corporate Alliances and Technology Transfer.

Proper citation: National Center for Marine Algae and Microbiota (RRID:SCR_002120) Copy   

•   Source: SciCrunch Registry

http://www.iris.edu/hq/

Passive and active source waveform data, event (earthquake) catalog, channel response data is available. This comprehensive data store of raw geophysical time-series data is collected from a large variety of sensors, courtesy of a vast array of US and International scientific networks, including seismometers (permanent and temporary), tilt and strain meters, infrasound, temperature, atmospheric pressure and gravimeters, to support basic research aimed at imaging the Earth's interior. IRIS also provides data and software for educational purposes. This consortium of over 100 US universities is dedicated to the operation of science facilities for the acquisition, management, and distribution of seismological data. IRIS programs contribute to scholarly research, education, earthquake hazard mitigation, and verification of the Comprehensive Nuclear-Test-Ban Treaty. Data is stored at the IRIS Data Management Center in Seattle, Washington. They currently manage a large archive from over tens of thousands of seismic stations and ship hundreds of terabytes of data yearly.

Proper citation: Incorporated Research Institutions for Seismology (RRID:SCR_002201) Copy   

•   Source: SciCrunch Registry

https://www.usap-dc.org/

Assists scientists in finding Antarctic scientific data of interest and submitting data for long-term preservation in accordance with their obligations under the National Science Foundation (NSF) Office of Polar Programs (OPP) Data Policy.

Proper citation: U.S. Antarctic Program Data Coordination Center (RRID:SCR_002221) Copy   

•   Source: SciCrunch Registry

http://www.earthchem.org/

Accepts and makes available geochemical, geochronlogical, and petrological data (analytical and synthesis) through this community-driven effort to facilitate the preservation, discovery, access and visualization of data generated. * PetDB holds geochemical data from sub-oceanic igneous and metamorphic rocks generated at mid-ocean ridges including back-arc basins, young seamounts, and old oceanic crust. Data are compiled primarily from the published literature. * SedDB integrates marine and terrestrial sediment geochemical data compiled primarily from the published literature. * Deep Lithosphere Data Set contains geochemical and petrological data from lower crust and upper mantle xenoliths. (more info) * VentDB contains hydrothermal spring geochemistry that hosts and serves the full range of compositional data acquired on seafloor hydrothermal vents from all tectonic settings. * NAVDAT - The Western North American Volcanic and Intrusive Rock Database * Geochron is an application that helps with the onerous task of data management for geochronological and thermochronological studies. * EarthChemPortal is the one-stop-shop for geochemical data that gives users the ability to search federated databases PetDB, NAVDAT, and GEOROC simultaneously, integrated into a common output format. (more info) * The EarthChem Library is a repository for geochemical datasets (analytical data, experimental data, synthesis databases) and other digital resources relevant to the field of geochemistry, contributed by the geochemistry community. * SESAR - System for Earth SAmple Registration

Proper citation: EarthChem (RRID:SCR_002207) Copy   

•   Source: SciCrunch Registry

http://metpetdb.rpi.edu/metpetweb/

Database / data repository for metamorphic petrology that is being designed and built by a global community of metamorphic petrologists in collaboration with computer scientists at Rensselaer Polytechnic Institute as part of the National Cyberinfrastructure Initiative.

Proper citation: MetPetDB (RRID:SCR_002208) Copy   

•   Source: SciCrunch Registry

http://csdms.colorado.edu/wiki/Main_Page

Model repository and data related to earth-surface dynamics modeling. The CSDMS Modeling Tool (CMT) allows you to run and couple CSDMS model components on the CSDMS supercomputer in a user-friendly software environment. Components in the CMT are based on models, originally submitted to the CSDMS model repository, and now adapted to communicate with other models. The CMT tool is the environment in which you can link these components together to run new simulations. The CMT software runs on your own computer; but it communicates with the CSDMS HPCC, to perform the simulations. Thus, the CMT also offers you a relatively easy way of using the CSDMS supercomputer for model experiments. CSDMS deals with the Earth's surface - the ever-changing, dynamic interface between lithosphere, hydrosphere, cryosphere, and atmosphere. They are a diverse community of experts promoting the modeling of earth surface processes by developing, supporting, and disseminating integrated software modules that predict the movement of fluids, and the flux (production, erosion, transport, and deposition) of sediment and solutes in landscapes and their sedimentary basins. CSDMS: * Produces protocols for community-generated, continuously evolving, open software * Distributes software tools and models * Provides cyber-infrastructure to promote the quantitative modeling of earth surface processes * Addresses the challenging problems of surface-dynamic systems: self-organization, localization, thresholds, strong linkages, scale invariance, and interwoven biology & geochemistry * Enables the rapid development and application of linked dynamic models tailored to specific landscape basin evolution (LBE) problems at specific temporal and spatial scales * Partners with related computational and scientific programs to eliminate duplication of effort and to provide an intellectually stimulating environment * Supports a strong linkage between what is predicted by CSDMS codes and what is observed, both in nature and in physical experiments * Supports the imperatives in Earth Science research

Proper citation: Community Surface Dynamics Modeling System (RRID:SCR_002196) Copy   

•   Source: SciCrunch Registry

http://www.neotomadb.org/

Paleoecology database for plio-pleistocene to holocene fossil data with a centralized structure for interdisciplinary, multiproxy analyses and common tool development; discipline-specific data can also be easily accessed. Data currently include North American Pollen (NAPD) and fossil mammals (FAUNMAP). Other proxies (plant macrofossils, beetles, ostracodes, diatoms, etc.) and geographic areas (Europe, Latin America, etc.) will be added in the near future. Data are derived from sites from the last 5 million years.

Proper citation: Neotoma Paleoecology Database (RRID:SCR_002190) Copy   

•   Source: SciCrunch Registry

http://www.ncdc.noaa.gov/paleo/softlib/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 12,2023. A simple, efficient, process-based forward model of tree-ring growth, requires as inputs only latitude and monthly temperature and precipitation.

Proper citation: VS-Lite (RRID:SCR_002431) Copy   

•   Source: SciCrunch Registry

http://connectomes.utah.edu/

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   

•   Source: SciCrunch Registry

http://www.crowdlabs.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cnas.ucr.edu/guppy/

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   

•   Source: SciCrunch Registry

http://www.plantontology.org

Ontology and database that links plant anatomy, morphology and growth and development to plant genomics data.Plant Ontology Consortium develops, curates and shares controlled vocabularies (ontologies) that describe plant structures and growth and developmental stages, providing semantic framework for meaningful cross species queries across databases. PO is under active development to expand to encompass terms and annotations from all plants.

Proper citation: Plant Ontology (RRID:SCR_006494) Copy   

•   Source: SciCrunch Registry