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http://nsidc.org/

National data center / repository for snow and ice data including snow, ice, glaciers, frozen ground, and climate interactions that make up Earth's cryosphere. The center manages and distributes scientific data, creates tools for data access, supports data users, performs scientific research, and educates the public about the cryosphere. Users may explore the Earth's frozen places in the collection of photographs and images. Photographs from field research trips, images captured by satellites of the changing cryosphere, and photos and images are available. Data sets are organized into the following groups: sea ice, frozen ground, snow cover, snow hydrology, glaciers and ice sheets, arctic people.

Proper citation: National Snow and Ice Data Center (RRID:SCR_002220) Copy   

•   Source: SciCrunch Registry

http://www.opentopography.org/

Accepts and provides access to high-resolution (meter to sub-meter scale) Earth science-oriented topography data (e.g. LiDAR) and bathymetric data, and related tools and resources. The OpenTopography Tool Registry provides a community populated clearinghouse of software, utilities, and tools oriented towards high-resolution topography data (e.g. collected with LiDAR technology) handling, processing, and analysis. Tools registered range from source code to full-featured software applications. Contributions to the registry via the Contribute a Tool page are welcome. OpenTopography also hosts a dataset catalog to which users can register datasets hosted elsewhere; these entries are discoverable by users alongside OpenTopography hosted datasets. Lidar point cloud data are available in LAS, LAZ and ASCII formats. Raster datasets and derived products can be downloaded in Arc ASCII, IMG, and GeoTIFF formats. Derived products and visualizations are available in Google Earth KML format. The OpenTopography user community and advisory committee provides feedback to define the scope of collaborations on data hosting and cyberinfrastructure development

Proper citation: OpenTopography (RRID:SCR_002204) Copy   

•   Source: SciCrunch Registry

http://www.bco-dmo.org/

Accepts and provides access to marine biogeochemical and ecological data sets from NSF-funded research programs. BCO-DMO is also the data repository for the US GLOBEC and JGOFS programs.

Proper citation: BCO-DMO (RRID:SCR_002191) Copy   

•   Source: SciCrunch Registry

https://repository.nced.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Field, laboratory, and model data related to earth-surface dynamics created or compiled by NCED-funded scientists. NCED is a Science and Technology Center developed to predict the coupled dynamics and co-evolution of landscapes and their ecosystems in order to transform management and restoration of the Earth-surface environment.

Proper citation: National Center for Earth-Surface Dynamics (RRID:SCR_002195) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/foldvillin

An archive of hundreds of all-atom, explicit solvent molecular dynamics simulations that were performed on a set of nine unfolded conformations of a variant of the villin headpiece subdomain (HP-35 NleNle). It includes scripts for accessing the archive of villin trajectories as well as a VMD plug-in for viewing the trajectories. In addition, all starting structures used in the trajectories are also provided. The simulations were generated using a distributed computing method utilizing the symmetric multiprocessing paradigm for individual nodes of the Folding_at_home distributed computing network. The villin trajectories in the archive are divided into two projects: PROJ3036 and PROJ3037. PROJ3036 contains trajectories starting from nine non-folded configurations. PROJ3037 contains trajectories starting from the native (folded) state. Runs 0 through 8 (in PROJ3036) correspond to starting configurations 0 through 8 discussed in the paper in J. Mol. Biol. (2007) 374(3):806-816 (see the publications tab for a full reference), whereas RUN9 uses the same starting configuration as RUN8. Each run contains 100 trajectories (named clone 0-99), each with the same starting configuration but different random velocities. Trajectories vary in their length of time and are subdivided into frames, also known as a generation. Each frame contains around 400 configurational snapshots, or timepoints, of the trajectory, with the last configurational snapshot of frame i corresponding to the first configurational snapshot of generation i+1. The goal is to allow researchers to analyze and benefit from the many trajectories produced through the simulations.

Proper citation: Molecular Simulation Trajectories Archive of a Villin Variant (RRID:SCR_002704) Copy   

•   Source: SciCrunch Registry

http://paleobiodb.org/

A non-governmental, non-profit public database for paleontological data providing researchers and the public with information about the entire fossil record. It has been organized and operated by a multi-disciplinary, multi-institutional, international group of paleobiological researchers. Its purpose is to provide global, collection-based occurrence and taxonomic data for organisms of all geological ages, as well data services to allow easy access to data for independent development of analytical tools, visualization software, and applications of all types. The Database's broader goal is to encourage and enable data-driven collaborative efforts that address large-scale paleobiological questions. Paleontological data files are accepted for upload. However, PaleoBioDB needs some basic data types to be included in order to perform an upload. The Application Programming Interface (API) gives scientists, students, and developers programmatic access to taxonomic, spatial, and temporal data contained within the database.

Proper citation: Paleobiology Database (RRID:SCR_003798) Copy   

•   Source: SciCrunch Registry

http://fold.it/

Foldit is a revolutionary new multiplayer online computer game that engages non-scientists in solving hard prediction problems, enabling you to contribute to important scientific research. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. Here are the basic principles to keep in mind when folding proteins. Your score on each protein is based on how well you do with these three things: # Pack the protein: The smaller the protein, the better. More precisely, you want to avoid empty spaces (voids) in the structure of the protein where water molecules can get inside. So you want the atoms in the protein to be as close together as possible. Certain structures, such as sheets, will even connect together with hydrogen bonds if you line them up right and get them close together. This is also good. Key word: Compact. # Hide the hydrophobics: Hydrophobics are the sidechains that don't want to be touching water, just like oil or wax. Since most proteins float around in water, you want to keep the hydrophobics (orange sidechains) surrounded by as many atoms as possible so the water won't get to them. The other side of this rule is that hydrophilics (blue sidechains) do want to be touching water, so they should be exposed as much as possible. Key word: Buried. # Clear the clashes: Two atoms can't occupy the same space at the same time. If you've folded a protein so two sidechains are too close together, your score will go down a lot. This is represented by a red spiky ball (clash) where the two sidechains are intersecting. If there are clashes, you know something is wrong with your protein. So make sure everything is far enough apart. Key word: Apart. The current series of Science Puzzles, the Grand Challenges, are meant to generate the evidence needed to prove that human protein folders can be more effective than computers at certain aspects of protein structure prediction. That's what all the puzzles in Foldit are about right now: predicting the structure of a protein based on its amino acid sequence. The three rules mentioned above describe the characteristics of correct protein structures.

Proper citation: Foldit (RRID:SCR_003788) Copy   

•   Source: SciCrunch Registry

http://www.uwyo.edu/buerkle/software/bamova/

Software that implements a Bayesian Analysis of Molecular Variance and different likelihood models for three different types of molecular data (including two models for high throughput sequence data).

Proper citation: bamova (RRID:SCR_000510) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/Urchin/contents.html

Laboratory modules designed for high school students covering sea urchin embryology including fertilization and development.

Proper citation: Sea Urchin Embryology (RRID:SCR_000460) Copy   

•   Source: SciCrunch Registry

http://www.cs.utah.edu/~miriah/pathline/Overview.html

Software visualization tool for comparative functional genomics that supports analysis of three types of biological data at once: functional data such as gene activity measurements; pathway data that presents a series of reactions within a cellular process; and phylogenetic data describing ancestral relationships between species. The design of Pathline includes two new visual encoding techniques. The first is an encoding of a linearized metabolic pathway representation that provides appropriate topological information and supports the comparison of quantitative data along the pathway. The second is a curvemap, a matrix layout of temporal expression data for enhanced perception of trends in gene and cell activity levels across multiple species.

Proper citation: Pathline (RRID:SCR_000635) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/LOVE

A versatile 1D, 2D and 3D data viewer geared for cross-platform visualization of stereotactic brain data. It is a 3-D viewer that allows volumetric data display and manipulation of axial, sagittal and coronal views. It reads Analyze, Raw-binary and NetCDF volumetric data, as well as, Multi-Contour Files (MCF), LWO/LWS surfaces, atlas hierarchical brain-region labelings ( Brain Trees). It is a portable Java-based software, which only requires a Java interpreter and a 64 MB of RAM memory to run on any computer architecture. LONI_Viz allows the user to interactively overlay and browse through several data volumes, zoom in and out in the axial, sagittal and coronal views, and reports the intensities and the stereo-tactic voxel and world coordinates of the data. Expert users can use LONI_Viz to delineate structures of interest, e.g., sulcal curves, on the 3 cardinal projections of the data. These curves then may be use to reconstruct surfaces representing the topological boundaries of cortical and sub-cortical regions of interest. The 3D features of the package include a SurfaceViewer and a full real-time VolumeRenderer. These allow the user to view the relative positions of different anatomical or functional regions which are not co-planar in any of the axial, sagittal or coronal 2D projection planes. The interactive part of LONI_Viz features a region drawing module used for manual delineation of regions of interest. A series of 2D contours describing the boundary of a region in projection planes (axial, sagittal or coronal) could be used to reconstruct the surface-representation of the 3D outer shell of the region. The latter could then be resliced in directions complementary to the drawing-direction and these complementary contours could be loaded in all tree cardinal views. In addition the surface object could be displayed using the SurfaceViewer. A pre-loading data crop and sub-sampling module allows the user to load and view practically data of any size. This is especially important when viewing cryotome, histological or stained data-sets which may reach 1GB (109 bytes) in size. The user could overlay several pre-registered volumes, change intensity colors and ranges and the inter-volume opacities to visually inspect similarities and differences between the different subjects/modalities. Several image-processing aids provide histogram plotting, image-smoothing, etc. Specific Features: * Region description DataBase * Moleculo-genetic database * Brain anatomical data viewer * BrainMapper tool * Surface (LightWave objects/scenes) and Volume rendering tools * Interactive Contour Drawing tool Implementation Issues: * Applet vs. Application - the software is available as both an applet and a standalone application. The former could be used to browse data from within the LONI database, however, it imposes restrictions on file-size, Internet connection and network-bandwidth and client/server file access. The later requires a local install and configuration of the LONI_Viz software * Extendable object-oriented code (Java), computer architecture independent * Complete online software documentation is available at http://www.loni.ucla.edu/LONI_Viz and a Java-Class documentation is available at http://www.loni.ucla.edu/~dinov/LONI_Vis.dir/doc/LONI_Viz_Java_Docs.html

Proper citation: LONI Visualization Tool (RRID:SCR_000765) Copy   

•   Source: SciCrunch Registry

http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   

•   Source: SciCrunch Registry

http://zoobank.org/

A database of scientific names in zoology. ZooBank is an online, open-access, community-generated registry for zoological nomenclature. It serves as a service to taxonomists, biologists, and the global diversity informatics community. It is the Official Register of the International Commission on Zoological Nomenclature (ICZN).

Proper citation: ZooBank (RRID:SCR_000901) Copy   

•   Source: SciCrunch Registry

http://lamp.icsi.berkeley.edu/lamp/

A software package for the inference of locus-specific ancestry in recently admixed populations. LAMP-LD takes the genotypes of admixed individuals as well as reference haplotype panels approximating the mixing ancestral populations, and outputs the estimated number of alleles from each ancestry in each locus for each individual. The LAMP-LD package also includes the program LAMP-HAP, which processes haplotype data when high-quality phasing is available, and utilizes trio nuclear family designs to improve estimation accuracy. LAMP-LD is based on a window-based processing combined within a hierarchical Hidden Markov Model. It can process 2,3 or 5 mixing populations, and its short per-sample processing time makes it suitable for analyzing large datasets of dense SNP panels. The original program LAMP does not use the LD and therefore is not as accurate, but it is useful in cases where the SNP density is not high enough or when the ancestral haplotypes are unkown.

Proper citation: Local Ancestry in adMixed Populations (RRID:SCR_001258) Copy   

•   Source: SciCrunch Registry

http://virome.diagcomputing.org/#view=home

A web-application designed for scientific exploration of metagenome sequence data collected from viral assemblages occurring within a number of different environmental contexts. The VIROME informatics pipeline focuses on the classification of predicted open-reading frames (ORFs) from viral metagenomes. The portal allows you to submit your viral metagenome to be processed through the VIROME analysis pipeline, and enable you to investigate your data via the VIROME user interface., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VIROME (RRID:SCR_004362) Copy   

•   Source: SciCrunch Registry

http://vamps.mbl.edu/overview.php

A publicly-accessible website to measure and visualize similarities and differences between molecular profiles of complex microbial communities. The project includes visualization tools such as heat maps that simultaneously compare the taxonomic distributions of multiple datasets and 3-D charts of the frequency distributions of 16S rRNA tags. Analytical tools include Chao diversity estimates and rarefaction curves. As a service to the community, researchers have the opportunity to upload their own data to the site for private viewing with the full range of data and analysis tools. Public data can be downloaded for further analysis locally.

Proper citation: VAMPS (RRID:SCR_004483) Copy   

•   Source: SciCrunch Registry

http://www.arabidopsis.org

Database of genetic and molecular biology data for the model higher plant Arabidopsis thaliana. Data available includes the complete genome sequence along with gene structure, gene product information, metabolism, gene expression, DNA and seed stocks, genome maps, genetic and physical markers, publications, and information about the Arabidopsis research community. Gene product function data is updated every two weeks from the latest published research literature and community data submissions. Gene structures are updated 1-2 times per year using computational and manual methods as well as community submissions of new and updated genes. TAIR also provides extensive linkouts from data pages to other Arabidopsis resources. The data can be searched, viewed and analyzed. Datasets can also be downloaded. Pages on news, job postings, conference announcements, Arabidopsis lab protocols, and useful links are provided.

Proper citation: TAIR (RRID:SCR_004618) Copy   

•   Source: SciCrunch Registry

http://www.aftol.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented Jan 13, 2022; To enhance the understanding of the evolution of the Kingdom Fungi, 1500+ species were sampled for eight gene loci across all major fungal clades, plus a subset of taxa for a suite of morphological and ultrastructural characters with resulting data: AFTOL Molecular Database (generated by WASABI - Web Accessible Sequence Analysis for Biological Inference), Blast search the AFTOL Database (generated by WASABI), AFTOL primers (generated by WASABI), AFTOL primers by species (generated by WASABI), AFTOL alignments, and the AFTOL Structural and Biochemical Database. Users may submit samples to the AFTOL project. AFTOL is a collaboration centered around four universities in the United States: Duke University (Francois Lutzoni and Rytas Vilgalys), Clark University (David Hibbett), Oregon State University (Joey Spatafora), and University of Minnesota (David McLaughlin). Participants throughout the world have donated vouchers, taxon samples, and gene sequences. The aim of the project is to reconstruct the fungal tree of life using all available data for eight loci (nuclear ribosomal DNA: LSU, SSU, ITS (including 5.8s, ITS1 and ITS2); RNA polymerase II: RPB1, RPB2; elongation factor 1-alpha; mitochondrial SSU rDNA, and mitochondrial ATP synthase protein subunit 6). A further objective of this study is to summarize and integrate current knowledge regarding fungal subcellular features within this new phylogenetic framework. The name of the bioinformatic package developed for AFTOL is WASABI which provides an efficient communication platform to facilitate the collection and dissemination of molecular data to (and from) the laboratories and participants. All molecular data can be viewed, downloaded, verified, and corrected by the participants of AFTOL. A central goal of the WASABI interface is to establish an automated analysis framework that includes basecalling of newly generated chromatograms, contig assembly, quality verification of sequences (including a local BLAST), sequence alignment, and congruence test. Gene sequences that pass all tests and are finally verified by their authors will undergo automated phylogenetic analysis on a regular schedule. Although all steps are initially carried out noninteractively, the users can verify and correct the results at any step and thus initiate the reanalysis of dependent data.

Proper citation: AFTOL (RRID:SCR_004650) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/brainsinsilicon/neurogrid.html

A specialized hardware platform that will perform cortex-scale emulations while offering software-like flexibility. With sixteen 12x14 sq-mm chips (Neurocores) assembled on a 6.5x7.5 sq-in circuit board that can model a slab of cortex with up to 16x256x256 neurons - over a million! The chips are interconnected in a binary tree by 80M spike/sec links. An on-chip RAM (in each Neurocore) and an off-chip RAM (on a daughterboard, not shown) softwire vertical and horizontcal cortical connections, respectively. It provides an affordable option for brain simulations that uses analog computation to emulate ion-channel activity and uses digital communication to softwire synaptic connections. These technologies impose different constraints, because they operate in parallel and in serial, respectively. Analog computation constrains the number of distinct ion-channel populations that can be simulatedunlike digital computation, which simply takes longer to run bigger simulations. Digital communication constrains the number of synaptic connections that can be activated per secondunlike analog communication, which simply sums additional inputs onto the same wire. Working within these constraints, Neurogrid achieves its goal of simulating multiple cortical areas in real-time by making judicious choices.

Proper citation: Neurogrid (RRID:SCR_005024) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.engineering.asu.edu/springs/Sprouts/index.html

SPROUTS is a database of predicted protein folding related data. It was designed to gather all the results from a study concerning the comparison between tools devoted to the prediction of stability changes upon point mutations. The second aim of this database is to offer simple and user-friendly tools to better visualize and analyze the results obtained. We are now able to propose three ways of visualization and analysis: the first one consists in getting raw Delta Delta G values in a table. The second one is a 2D graph representation of a computed stability score for each residue of a given sequence and for each tool. The last one is based on a Jmol applet (Jmol) with the possibility to represent the 3D structure of a given protein with symbols representing the information stored in the database. We assume that each visualization mode offers a different look on the data stored in the database and will suit to every scientists willing to query the database whether they are more used to handle 3D protein structure or 1D/2D sequence problems. Finally, the ultimate objective is to integrate these data and their analysis with other structural bioinformatic concepts in order to improve other methods that may be related to this concept. We are currently working at adding the information extracted from our other projects related to the prediction of protein folding nucleus in order to obtain a meta server devoted to the characterization of the folding core of proteins. As of today, this database has grown up and consists in more than 100 structures which have been computed for a total of around 16500 amino acids.

Proper citation: SPROUTS- Structural Prediction for Protein Folding Utility System (RRID:SCR_005118) Copy   

•   Source: SciCrunch Registry