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http://www.ncbi.nlm.nih.gov/gene/about-generif

A database and annotation tool that provides a simple mechanism to allow scientists to add to the functional annotation of genes described in Gene. To be processed, a valid Gene ID must exist for the specific gene, or the Gene staff must have assigned an overall Gene ID to the species. The latter case is implemented via records in Gene with the symbol NEWENTRY.

Proper citation: Gene Reference into Function (RRID:SCR_003436) Copy   

•   Source: SciCrunch Registry

http://www.nihclinicalcollection.com

A plated array of approximately 450 small molecules that have a history of use in human clinical trials. The collection was assembled by the National Institutes of Health (NIH) through the Molecular Libraries Roadmap Initiative as part of its mission to enable the use of compound screens in biomedical research. Similar collections of FDA approved drugs have proven to be rich sources of undiscovered bioactivity and therapeutic potential. The clinically tested compounds in the NCC are highly drug-like with known safety profiles. These compounds can provide excellent starting points for medicinal chemistry optimization and, for high-affinity targets, may even be appropriate for direct human use in new disease areas.

Proper citation: NIH Clinical Collection (RRID:SCR_007349) Copy   

•   Source: SciCrunch Registry

http://www.project-redcap.org/

Web application that allows users to build and manage online surveys and databases. Using REDCap's stream-lined process for rapidly developing projects, you may create and design projects using 1) the online method from your web browser using the Online Designer; and/or 2) the offline method by constructing a "data dictionary" template file in Microsoft Excel, which can be later uploaded into REDCap. Both surveys and databases (or a mixture of the two) can be built using these methods. REDCap provides audit trails for tracking data manipulation and user activity, as well as automated export procedures for seamless data downloads to Excel, PDF, and common statistical packages (SPSS, SAS, Stata, R). Also included are a built-in project calendar, a scheduling module, ad hoc reporting tools, and advanced features, such as branching logic, file uploading, and calculated fields. REDCap has a quick and easy software installation process, so that you can get REDCap running and fully functional in a matter of minutes. Several language translations have already been compiled for REDCap (e.g. Chinese, French, German, Portuguese), and it is anticipated that other languages will be available in full versions of REDCap soon. The REDCap Shared Library is a repository for REDCap data collection instruments and forms that can be downloaded and used by researchers at REDCap partner institutions.

Proper citation: REDCap (RRID:SCR_003445) Copy   

•   Source: SciCrunch Registry

https://www.teamtat.org

Web based collaborative text annotation tool. Used for managing multi-user, multi-label document annotation. Project managers can specify annotation schema for entities and relations and select annotators and distribute documents anonymously to prevent bias. Document input format can be plain text, PDF or BioC (uploaded locally or automatically retrieved from PubMed/PMC), and output format is BioC with inline annotations. Displays figures from full text.

Proper citation: TeamTat (RRID:SCR_023439) Copy   

•   Source: SciCrunch Registry

http://mind.loni.usc.edu

The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.

Proper citation: LONI MiND (RRID:SCR_004820) Copy   

•   Source: SciCrunch Registry

https://github.com/VH-Lab/vhlab-microscopyimageanalysis-matlab

Software Matlab app for analysis of high density imaging data like that from Array Tomography.

Proper citation: vhlab-microscopyimageanalysis-matlab (RRID:SCR_024450) Copy   

•   Source: SciCrunch Registry

http://ccb.jhu.edu/software/glimmerhmm/

A gene finder based on a Generalized Hidden Markov Model (GHMM). Although the gene finder conforms to the overall mathematical framework of a GHMM, additionally it incorporates splice site models adapted from the GeneSplicer program and a decision tree adapted from GlimmerM. It also utilizes Interpolated Markov Models for the coding and noncoding models . Currently, GlimmerHMM's GHMM structure includes introns of each phase, intergenic regions, and four types of exons (initial, internal, final, and single).

Proper citation: GlimmerHMM (RRID:SCR_002654) Copy   

•   Source: SciCrunch Registry

http://neurospy.org

neurospy is a free software for functional imaging of fast neuronal activity. neurospy is a modular cross-platform application framework written in Java for the NetBeans Platform. At this time it runs on Windows XP-based LeCroy oscilloscopes and drives acousto-optic scanners via USB using the Analog Devices 9959 Direct Digital Synthesis chip. This combination makes one of the most powerful systems for scanning microscopy available today at any price. neurospy is very easy to port to other kinds of acquisition and scanning hardware.

Proper citation: neurospy (RRID:SCR_007016) Copy   

•   Source: SciCrunch Registry

http://www.sb.fsu.edu/~rsref/Distribution/roadmap_distribution.htm

Software tool to display surface of macromolecule and its properties. Uses projections to map van der Waals or solvent accessible surface of macromolecule onto plane., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Roadmap (RRID:SCR_017207) Copy   

•   Source: SciCrunch Registry

https://www.jax.org/research-and-faculty/resources/knockout-mouse-project/high-throughput-production

Project is providing critical tools for understanding gene function and genetic causes of human diseases. Project KOMP is focused on generating targeted knockout mutations in mouse ES cells. Second phase, KOMP2, relies upon successful generation of strains of knockout mice from these ES cells. Information from JAX about their contributions to KOMP project.

Proper citation: Knockout Mouse Project (RRID:SCR_005571) Copy   

•   Source: SciCrunch Registry

http://nhprtr.org/

Nonhuman Primate reference transcriptome resource consisting of deep sequencing complete transcriptomes (RNA-seq) from multiple NHP species.

Proper citation: Nonhuman Primate Reference Transcriptome Resource (RRID:SCR_017534) Copy   

•   Source: SciCrunch Registry

https://cic.ini.usc.edu/

Project to create complete mesoscale connectivity atlas of the C57Black/6 mouse brain and to subsequently generate its global neural networks.

Proper citation: Mouse Connectome Project (RRID:SCR_017313) Copy   

•   Source: SciCrunch Registry

http://www.compucell3d.org/

Open-source simulation environment for multi-cell, single-cell-based modeling of tissues, organs and organisms. It uses Cellular Potts Model to model cell behavior.

Proper citation: CompuCell3D (RRID:SCR_003052) Copy   

•   Source: SciCrunch Registry

https://github.com/jefftc/changlab

Software system for performing bioinformatics analyses. System includes knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. Backwards-chaining rule-based expert system comprised of data model that can capture richness of biological data, and inference engine that reasons on knowledge base to produce workflows. Knowledge base is populated with rules to analyze microarray and next generation sequencing data.

Proper citation: BETSY (RRID:SCR_026239) Copy   

•   Source: SciCrunch Registry

http://udn.nichd.nih.gov/brainatlas_home.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 1, 2019. The first brain atlas for the common marmoset to be made available since a printed atlas by Stephan, Baron and Schwerdtfeger published in 1980. It is a combined histological and magnetic resonance imaging (MRI) atlas constructed from the brains of two adult female marmosets. Histological sections were processed from Nissl staining and digitized to produce an atlas in a large format that facilitates visualization of structures with significant detail. Naming of identifiable brain structures was performed utilizing current terminology. For the present atlas, an adult female was perfused through the heart with PBS followed by 10% formalin. The brain was then sent to Neuroscience Associates of Knoxville, TN, who prepared the brain for histological analysis. The brain was cut in the coronal (frontal) plane at 40 microns, every sixth section stained for Nissl granules with thionine and every seventh section stained for myelinated fibers with the Weil technique. The mounted sections were photographed at the NIH (Medical Arts and Photography Branch). The equipment used was a Nikon Multiphot optical bench with Zeiss Luminar 100 mm lens, and scanned with a Better Light 6100 scan back driven by Better Light Viewfinder 5.3 software. The final images were saved as arrays of 6000x8000 pixels in Adobe Photoshop 6.0. A scale in mm provided with these images permitted construction of the final Nissl atlas files with a horizontal and vertical scale. Some additional re-touching (brightness and contrast) was done with Adobe Photoshop Elements 2.0. The schematic (labeled) atlas plates were created from the Nissl images. The nomenclature came almost exclusively from brainmaps.org, where a rhesus monkey brain with structures labeled can be found. The labels for the MRI images were placed by M. R. Zametkin, under supervision from Dr. Newman.

Proper citation: Brain atlas of the common marmoset (RRID:SCR_005135) 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://videocast.nih.gov/

VideoCasting of special NIH events, seminars, conferences, meetings and lectures available to viewers on the NIH network and the Internet from the VideoCast web site. VideoCasting is the method of electronically streaming digitally encoded video and audio data from a server to a client. VideoCast is often referred to as streaming video. Streaming files are not downloaded, but rather are broadcast in a manner similar to television broadcasts. The videos are processed by a compression program into a streaming format and delivered in a staggered fashion to minimize impact upon the network and maximize the experience of the content for the viewer. When users request a streaming file they will receive an initial burst of data after a short delay (file latency). While content is being viewed, the streaming server machine and software continues to stream data in such a manner that the viewer experiences no break in the content. CIT can broadcast your seminar, conference or meeting live to a world-wide audience over the Internet as a real-time streaming video. The event can be recorded and made available for viewers to watch at their convenience as an on-demand video or a downloadable podcast. CIT can also broadcast NIH-only or HHS-only content.

Proper citation: NIH VideoCasting (RRID:SCR_001885) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://ccdb.ucsd.edu/SAO

Ontology that describes structures from the dimensional range encompassing cellular and subcellular structure, supracellular domains, and macromolecules. It is built according to ontology development best practices (re-use of existing ontologies; formal definitions of terms; use of foundational ontologies). It describes the parts of neurons and glia and how these parts come together to define supracellular structures such as synapses and neuropil. Molecular specializations of each compartment and cell type are identified. The SAO was designed with the goal of providing a means to annotate cellular and subcellular data obtained from light and electron microscopy, including assigning macromolecules to their appropriate subcellular domains. The SAO thus provides a bridge between ontologies that describe molecular species and those concerned with more gross anatomical scales. Because it is intended to integrate into ontological efforts at these other scales, particular care was taken to construct the ontology in a way that supports such integration.

Proper citation: Subcellular Anatomy Ontology (RRID:SCR_003486) Copy   

•   Source: SciCrunch Registry