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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

http://fatcat.burnham.org/

Web server for flexible protein structure comparison. Structure alignment is formulated as the aligned fragment pairs chaining process allowing at most t twists, and the flexible structure alignment is transformed into a rigid structure alignment when t is forced to be 0., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: FATCAT (RRID:SCR_014631) Copy   

•   Source: SciCrunch Registry

http://cellorganizer.org

Image analysis software that learns modular models of things such as cell shape, nuclear shape, vesicular organelle distribution and microtubule distribution directly from 2D or 3D images and can produce specific instances of cell geometries without the need to create them by hand or to segment microscope images. These geometries can be combined with biochemical models to perform spatially realistic cell simulations if used in conjunction with MCell.

Proper citation: CellOrganizer (RRID:SCR_014828) Copy   

•   Source: SciCrunch Registry

https://elegansvariation.org/

Supplier and researcher of wild C. elegans strains. CeNDR supplies organisms, analyzes whole-genome sequences, and facilitates genetic mappings to aid researchers in gene discovery.

Proper citation: Caenorhabditis elegans Natural Diversity Resource (CeNDR) (RRID:SCR_014958) Copy   

•   Source: SciCrunch Registry

http://www.chlamycollection.org/

Central repository that receives, catalogs, preserves, and distributes wild type and mutant cultures of the green alga Chlamydomonas reinhardtii, as well as useful molecular reagents and kits for education and research.

Proper citation: Chlamydomonas Resource Center (RRID:SCR_014960) 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://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

https://brainlife.io/

Free cloud platform for secure neuroscience data analysis. Allows to manage data, processing and results, sharing projects privately with collaborators or publicly with brainlife.io community.Promotes engagement and education in reproducible neuroscience.You can share your neuroimaging data publicly or privately. Data on brainlife.io is organized as Datatypes to allow interoperability between Apps.

Proper citation: brainlife (RRID:SCR_020940) Copy   

•   Source: SciCrunch Registry

http://www.data.scec.org/

Archive of earthquake data for research in seismology and earthquake engineering in Southern California recorded or processed by the Southern California Seismic Network (SCSN). Users can access information on: * Recent earthquakes detected by the SCSN * Significant southern California earthquakes and faults * The southern California earthquake catalog, spanning from 1933 to present * Waveform and metadata files of SCSN seismic stations from 1977 to present * Data sets created by SCEC scientists to assist in ongoing and future research

Proper citation: Southern California Earthquake Data Center (RRID:SCR_000663) Copy   

•   Source: SciCrunch Registry

http://www.bindingdb.org

Web accessible database of data extracted from scientific literature, focusing on proteins that are drug-targets or candidate drug-targets and for which structural data are present in Protein Data Bank . Website supports query types including searches by chemical structure, substructure and similarity, protein sequence, ligand and protein names, affinity ranges and molecular weight . Data sets generated by BindingDB queries can be downloaded in form of annotated SDfiles for further analysis, or used as basis for virtual screening of compound database uploaded by user. Data are linked to structural data in PDB via PDB IDs and chemical and sequence searches, and to literature in PubMed via PubMed IDs .

Proper citation: BindingDB (RRID:SCR_000390) Copy   

•   Source: SciCrunch Registry

http://criticalzone.org/

Data related to the National Critical Zone Observatory Program including in-situ environmental sensors, field instruments, remote sensing, and surface and subsurface imaging. The Program serves the international scientific community through research, infrastructure, data, and models. They focus on how components of the Critical Zone interact, shape Earth's surface, and support life. A primary goal is to develop high-resolution 4D datasets that inform our theoretical framework, constrain our conceptual and coupled systems models, and test our model-generated hypotheses. They are developing cross-CZO capabilities to easily share, integrate, analyze and preserve the wide range of multi-disciplinary data generated by CZOs.

Proper citation: Critical Zone Observatories (RRID:SCR_002199) Copy   

•   Source: SciCrunch Registry

http://www.marine-geo.org/portals/seismic/

Seismic Reflection Field Data from the academic research community. Their partner Academic Seismic Portal at UTIG offers additional seismic resources, http://www.ig.utexas.edu/sdc/

Proper citation: Academic Seismic Portal at LDEO (RRID:SCR_002194) Copy   

•   Source: SciCrunch Registry

http://www.ornisnet.org/

ORNIS is a database of bird specimens as well as a portal to connect the academic and museum communities involved with studying birds. This project expands on existing infrastructure developed for distributed mammal (MaNIS), amphibian and reptile (HerpNet), and fish (FishNet) databases. Over 5 million bird specimens are housed in North American collections, documenting the composition, distribution, ecology, and systematics of the world's estimated 10,000-16,000 bird species. Millions of additional observational records are held in diverse data sets. ORNIS addresses the urgent call for increased access to these data in an open and collaborative manner, and involves development of a suite of online software tools for data analysis and error-checking. This project expands on existing infrastructure developed for distributed mammal (MaNIS), amphibian and reptile (HerpNet), and fish (FishNet) databases. Improved access to avian data sets will allow predictive uses to reveal patterns and processes of evolutionary and ecological phenomena that have not been apparent heretofore. Along with similar infrastructures for other vertebrate groups, it also will enable detailed and synthetic knowledge of the earth's biodiversity for tracking climate change, emerging diseases (e.g., West Nile Virus), and other conservation challenges for species in the 21st century.

Proper citation: ORNIS (RRID:SCR_002896) Copy   

•   Source: SciCrunch Registry

http://www.genes2cognition.org/db/Search

Database of protein complexes, protocols, mouse lines, and other research products generated from the Genes to Cognition project, a project focused on understanding molecular complexes involved in synaptic transmission in the brain.

Proper citation: Genes to Cognition Database (RRID:SCR_002735) Copy   

•   Source: SciCrunch Registry

http://sonorus.princeton.edu/hefalmp/

HEFalMp (Human Experimental/FunctionAL MaPper) is a tool developed by Curtis Huttenhower in Olga Troyanskaya's lab at Princeton University. It was created to allow interactive exploration of functional maps. Functional mapping analyzes portions of these networks related to user-specified groups of genes and biological processes and displays the results as probabilities (for individual genes), functional association p-values (for groups of genes), or graphically (as an interaction network). HEFalMp contains information from roughly 15,000 microarray conditions, over 15,000 publications on genetic and physical protein interactions, and several types of DNA and protein sequence analyses and allows the exploration of over 200 H. sapiens process-specific functional relationship networks, including a global, process-independent network capturing the most general functional relationships. Looking to download functional maps? Keep an eye on the bottom of each page of results: every functional map of any kind is generated with a Download link at the bottom right. Most functional maps are provided as tab-delimited text to simplify downstream processing; graphical interaction networks are provided as Support Vector Graphics files, which can be viewed using the Adobe Viewer, any recent version of Firefox, or the excellent open source Inkscape tool.

Proper citation: Human Experimental/FunctionAL MaPper: Providing Functional Maps of the Human Genome (RRID:SCR_003506) Copy   

•   Source: SciCrunch Registry

http://biosearch.berkeley.edu/

Developed as part of the BioText project at the University of California, Berkeley, the BioText Search Engine is a freely available Web-based application that provides biologists with new ways to access the scientific literature. The system indexes all open access articles available at PubMed Central. New articles are indexed daily. The current collection consists of more than 300 journals, 40,000 articles, 100,000 figures, and 60,000 tables. The Full Text & Abstract view searches the full text of articles (in addition to title, author, and abstract information) and returns full-text excerpts that match users' queries. Three selection boxes at the top (ABSTRACTS, FULL-TEXT EXCERPTS and FIGURES allow users to choose what the view displays. The BioText Search Engine allows users to search in tables. When the table view is selected, BioText searches in article titles, table captions, and table contents. The Grid View allows users to search over captions. It returns figures and truncated captions in a grid arrangement.

Proper citation: BioText Search Engine (RRID:SCR_003600) Copy   

•   Source: SciCrunch Registry

http://cmr.jcvi.org/cgi-bin/CMR/shared/GenomePropertiesHomePage.cgi

The Genome Properties system consists of a suite of Properties which are carefully defined attributes of prokaryotic organisms whose status can be described by numerical values or controlled vocabulary terms for individual completely sequenced genomes. The system has been designed to capture the widest possible range of attributes and currently encompasses taxonomic terms, genometric calculations, metabolic pathways, systems of interacting macromolecular components and quantitative and descriptive experimental observations (phenotypes) from the literature. You may search the Genome Properties Database in 1 of 3 ways: * Search For Predicted Properties in the CMR: The Genome Property Search allows you to search the Genome Property database for state information for selected genomes and properties. * Perform a Keyword Search for a Specific Property: Lists all Genome Properties that match a specific text string. You can choose to search All Fields within a genome property or the Property Name. * Browse Top Level Genome Properties: Click on the properties to see the specific genome property report page. The Genome Properties system presents key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny and computational analyses. The results of searches using hidden Markov models allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports and other forms of evidence. Genome Properties system was applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties.

Proper citation: JCVI GenProp (RRID:SCR_004592) Copy   

•   Source: SciCrunch Registry

http://pilgrm.princeton.edu

PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.

Proper citation: PILGRM (RRID:SCR_004749) Copy   

•   Source: SciCrunch Registry