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https://github.com/KarrLab/de_sim

Software object oriented discrete event simulation tool for complex, data driven modeling. Open source, Python based object oriented discrete event simulation tool that makes it easy to use large, heterogeneous datasets and high level data science tools such as NumPy, Scipy, pandas, and SQLAlchemy to build and simulate complex computational models.

Proper citation: DE-Sim (RRID:SCR_018770) Copy   

•   Source: SciCrunch Registry

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

Repository providing free access to marine geophysical data (e.g. bathymetry, seismic data, magnetics, gravity, images) and related land-based data from NSF-funded research conducted throughout the global oceans. Data Portals include GeoPRISMS, MARGINS, Ridge 2000, Antarctic and Southern Ocean Data Synthesis, the Global Multi-Resolution Topography Synthesis, and Seismic Reflection Field Data Portal. Primary data types served are multibeam bathymetric data from the ocean floor, seismic reflection data imaging below the seafloor, and multi-disciplinary ship based data from the Southern Ocean. Other holdings include deep-sea photographic transects, and ultra-high resolution bathymetry, temperature probe data, biological species compilations, MAPR and CTD data. Derived data products and sets include microseismicity catalogs, images, visualization scenes, magnetic and gravity compilations, grids of seismic layer thickness, velocity models, GIS project files, and 3D visualizations. Tools to discover, explore, and visualize data are available. They deliver catalogs, maps, and data through standard programmatic interfaces. GeoMapApp, a standalone data visualization and analysis tool, permits dynamic data exploration from a map interface and the capability to generate and download custom grids and maps and other data. Through GeoMapApp, users can access data hosted at the MGDS, at other data repositories, and import their own data sets. Global Multi-Resolution Topography (GMRT) is a continuously-updated compilation of seafloor bathymetry integrated with global land topography. It can be used to create maps and grids and it can be accessed through several standard programmatic interfaces including GeoMapApp and Google Earth. The GMRT compilation can also be explored in 3D using Virtual Ocean. The MGDS MediaBank contains high quality images, illustrations, animations and video clips that are organized into galleries. Media can be sorted by category, and keyword and map-based search options are provided. Each item in the MediaBank is accompanied by metadata that provides access to a cruise catalog and data repository.

Proper citation: Marine Geoscience Data System (RRID:SCR_002164) Copy   

•   Source: SciCrunch Registry

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://www.qgene.org/

A free, open-source, computationally efficient Java program for comparative analyses of QTL mapping data and population simulation that runs on any computer operating system. (entry from Genetic Analysis Software) It is written with a plug-in architecture for ready extensibility. The software accommodates line-cross mating designs consisting of any arbitrary sequence of selfing, backcrossing, intercrossing and haploid-doubling steps that includes map, population, and trait simulators; and is scriptable. Source code is available on request.

Proper citation: QGene (RRID:SCR_003209) 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

https://github.com/slowkoni/rfmix

Software tool for local ancestry and admixture inference. Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference.

Proper citation: RFMix (RRID:SCR_027030) Copy   

•   Source: SciCrunch Registry

https://zenodo.org/records/11095105

Software label transfer tool for single-cell RNA sequencing analysis. Scalable, Interpretable Modeling for Single-cell RNA-seq data classification.

Proper citation: SIMS (RRID:SCR_025787) Copy   

•   Source: SciCrunch Registry

https://github.com/mwang87/MassQueryLanguage

Software application for universal searching of Mass Spectrometry data. Open source MS query language for flexible and mass spectrometer manufacturer-independent mining of MS data. Implements common MS terminology to build consensus vocabulary to search for MS patterns in single mass spectrometry run. Enables set of mass spectrometry patterns to be queried directly from raw data.

Proper citation: MassQL (RRID:SCR_025106) Copy   

•   Source: SciCrunch Registry

https://fmug.amaral.northwestern.edu/

Software data-driven tool to identify understudied genes and characterize their tractability. Users submit list of human genes and can filter these genes down based on list of factors. Code to generate Find My Understudied Genes app for Windows, iOS and macOS platforms.

Proper citation: Find My Understudied Genes (RRID:SCR_025047) Copy   

•   Source: SciCrunch Registry

https://github.com/TonnesenLab/Diffusion-Model/

Software code for simulating diffusion in brain extracellular space images.

Proper citation: Diffusion-Model (RRID:SCR_027942) Copy   

•   Source: SciCrunch Registry

http://www.mbl.org/mbl_main/atlas.html

High-resolution electronic atlases for mouse strains c57bl/6j, a/j, and dba/2j in either coronal or horizontal section. About this Atlas: The anterior-posterior coordinates are taken from an excellent print atlas of a C57BL/6J brain by K. Franklin and G. Paxinos (The Mouse Brain in Stereotaxic Coordinates, Academic Press, San Diego, 1997, ISBN Number 0-12-26607-6; Library of Congress: QL937.F72). The abbreviations we have used to label the sections conform to those in the Franklin-Paxinos atlas. A C57BL/6J mouse brain may contain as many as 75 million neurons, 23 million glial cells, 7 million endothelial cells associated with blood vessels, and 3 to 4 million miscellaneous pial, ependymal, and choroid plexus cells (see data analysis in Williams, 2000). We have not yet counted total cell number in DBA/2J mice, but the counts are probably appreciably lower.The brain and sections were all processed as described in our methods section. The enlarged images have a pixel count of 1865 x 1400 and the resolution is 4.5 microns/pixel for the processed sections.Plans: In the next several years we hope to add several additional atlases of the same sort for other strains of mice. A horizontal C57BL/6J atlas and a DBA/2J coronal atlas were completed by Tony Capra, summer 2000, and additional atlases may be made over the next several years. As describe in the MBL Procedures Section is not hard to make your own strain-specific atlas from the high resolution images in the MBL.

Proper citation: Mouse Brain Atlases (RRID:SCR_007127) 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.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

http://www.archive.org/

An Internet library offering the general public access to historical collections that exist in digital format including texts, audio, moving images, and software. Additionally it provides archived web pages in their collections, and specialized services for adaptive reading and information access for the blind and other persons with disabilities. Founded in 1996 and located in San Francisco, the Archive has been receiving data donations from Alexa Internet and others. In late 1999, the organization started to grow to include more well-rounded collections.

Proper citation: Internet Archive (RRID:SCR_001682) Copy   

•   Source: SciCrunch Registry

http://www.genes2cognition.org/resources/

Biological resources, including gene-targeting vectors, ES cell lines, antibodies, and transgenic mice, generated for its phenotyping pipeline as part of the Genes to Cognition research program are freely-available to interested researchers. Available Transgenic Mouse Lines: *Hras1 (H-ras) knockout,C57BL/6J *Dlg4 (PSD-95) knockout,129S5 *Dlg4 (PSD-95) knockout,C57BL/6J *Dlg3 (SAP102) knockout with hprt mutation,129S5 *Dlg3 (SAP102) knockout (wild-type for hprt,C57BL/6J *Syngap1 (SynGAP) knockout (from 8.24 clone), C57BL/6J *Dlg4 (PSD-95) guanylate kinase domain deletion, C57BL/6J *Ptk2 (FAK) knockout,C57BL/6J

Proper citation: Genes to Cognition - Biological Resources (RRID:SCR_001675) Copy   

•   Source: SciCrunch Registry

http://nashua.case.edu/PathwaysWeb/Web/

An integrated software system for storing, managing, analyzing, and querying biological pathways at different levels of genetic, molecular, biochemical and organismal detail. The system contains a pathways database and associated tools to store, compare, query, and visualize metabolic pathways. The aim is to develop an integrated database and the associated tools to support computational analysis and visualization of biochemical pathways. At the computational level, PathCase allows users to visualize pathways in multiple abstraction levels, and to pose predetermined and ad hoc queries using a graphical user interface. Pathways are represented as graphs, and implemented as a relational database. The available functional annotations include the identity of the substrate(s), product(s), cofactors, activators, inhibitors, enzymes or other processing molecules, GO-categories of enzymes (as well as GO hierarchy visualizations two-way-linked to PathCase enzymes), EC number information and the associated links, and synonyms and encoding genes of gene products.

Proper citation: PathCase Pathways Database System (RRID:SCR_001835) Copy   

•   Source: SciCrunch Registry

http://www.plantgdb.org/AtGDB/

Database providing a sequence-centered genome view for Arabidopsis thaliana, with a narrow focus on gene structure annotation. The current genome assembly displayed at AtGDB is version TAIR9. Annotated gene models are TAIR10. They have mapped the complete set of 176,915 publicly available Arabidopsis EST sequences onto the Arabidopsis genome using GeneSeqer, a spliced alignment program incorporating sequence similarity and splice site scoring. About 96% of the available ESTs could be properly aligned with a genomic locus, with the remaining ESTs deriving from organelle genomes and non-Arabidopsis sources or displaying insufficient sequence quality for alignment. The mapping provides verified sets of EST clusters for evaluation of EST clustering programs. Analysis of the spliced alignments suggests corrections to current gene structure annotation and provides examples of alternative and non-canonical pre-mRNA splicing.

Proper citation: Arabidopsis thaliana Genome Database (RRID:SCR_001901) 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://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