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http://www.nihtoolbox.org/WhatAndWhy/Sensation/Olfaction/Pages/NIH-Toolbox-Odor-Identification-Test.aspx

Assessment test to assess a person's ability to identify various odors. Participants use scratch 'n' sniff cards and after scratching them one at a time, are asked to identify which of four pictures on the computer screen matches the odor they have just smelled. Participants ages 10-85 are administered nine odor cards, while those ages 3-9 are administered five odor cards. Child participants (ages 3 -9 years) are first asked to identify the eight pictures that are used as answer choices, to ensure they can complete the task. Having identified the pictures, they are asked if they have tasted or smelled the objects or foods depicted. This test takes approximately 4 to 5 minutes to administer and is recommended for ages 3-85.

Proper citation: NIH Toolbox Odor Identification Test (RRID:SCR_003634) Copy   

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http://sccn.ucsd.edu/wiki/MPT

This toolbox is an EEGLAB plugin for performing Measure Projection Analysis. Measure Projection Analysis (MPA) is a novel probabilistic multi-subject inference method that overcomes EEG Independent Component (IC) clustering issues by abandoning the notion of distinct IC clusters. Instead, it searches voxel by voxel for brain regions having event-related IC process dynamics that exhibit statistically significant consistency across subjects and/or sessions as quantified by the values of various EEG measures. Local-mean EEG measure values are then assigned to all such locations based on a probabilistic model of IC localization error and inter-subject anatomical and functional differences.

Proper citation: Measure Projection Toolbox (RRID:SCR_002429) Copy   

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http://www.w3.org/wiki/images/5/51/HCLSIG$$SWANSIOC$$Actions$$RhetoricalStructure$$models$$abcde$abcde_example.htm

Proposed format for papers to be machine-readable for computers and wikis. The goal is to make mining, integration, and consumption of published information by semantic browsers and wikis easier.

Proper citation: ABCDE Format (RRID:SCR_002428) Copy   

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http://www.catstests.com/Product07.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. The modifiable n-Back test is free software presumed to measure executive control of the updating of information in working memory. The task requires the participant to monitor some dimension (e.g. content, position, numerosity) of a temporally present sequence of items, responding when the currently presented item matches on the relevant dimension an item that was just recently presented. The match can be with an item present either 1 back, 2 back, 3 back or n back. Considerable flexibility is provided to the experimenter in specifying various parameters of the experiment (e.g. presentation rate, n back, content, position, color). The n-Back test is presumed to measure executive control of the updating of information in working memory. (Shimamura, 2000) Watter, Geffen and Geffen (2001) based on their work with the P300 event-related-potential have suggested that the n-Back is a dual task in that latencies of the P300 did not change with increasing task difficulty, that is memory load while amplitude did reflecting in their view a reallocation of attention and processing capacity away from the matching subtask. The n-Back task is one in which the participant is presented a series of stimuli at a constant rate. The task of the participant is to determine if the currently presented stimulus is similar (along some dimension) to one they have recently (usually one, two or three positions back) seen in the stream. Match criteria can be dimensions like material, position on the screen, color or some combination. CATs n-Back allows for substantial control over the position in which the material is presented (nine different positions), the nature of the material (any character or dingbat string, and any color. The experimenter can set the speed at which the sequence is presented including both the stimulus on time and the inter-stimulus interval. Participant responses can be made either using the keyboard or the mouse. At this time no normative data is available for this test.

Proper citation: Colorado Assessment Tests: n-Back (RRID:SCR_003517) Copy   

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https://sites.google.com/a/brain.org.au/ctp/

Software package with functions that will help researchers plan how many subjects per group need to be included in an MRI-based cortical thickness study to ensure a thickness difference is detected. The package requires cortical thickness mapping and co-registration to be carried out using Freesurfer. The power analyses are implemented in the R software package., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: cortex (RRID:SCR_002467) Copy   

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http://portal.ncibi.org/gateway/saga.html

SAGA (Substructure Index-based Approximate Graph Alignment) is a tool for querying a biological graph database to retrieve matches between subgraphs of molecular interactions and biological networks. SAGA implements an efficient approximate subgraph matching algorithm that can be used for a variety of biological graph matching problems such as the pathway matching SAGA uses to compare pathways in KEGG and Reactome. You can also use SAGA to find matches in literature databases that have been parsed into semantic graphs. In this use of SAGA, portions of PubMed have been parsed into graphs that have nodes representing gene names. A link is drawn between two genes if they are discussed in the same sentence (indicating there is potential association between the two genes). SAGA lets you match graphs between different databases even though the content is distinct and the databases organize pathways in different ways. This cross-database matching is achieved by SAGA's flexible approximate subgraph matching model that computes graph similarity, and allows for node gaps, node mismatches, and graph structural differences. Comparing pathways from different databases can be a useful precursor to pathway data integration. SAGA is very efficient for querying relatively small graphs, but becomes prohibitory expensive for querying large graphs. Large graph data sets are common in many emerging database applications, and most notably in large-scale scientific applications. To fully exploit the wealth of information encoded in graphs, effective and efficient graph matching tools are critical. Due to the noisy and incomplete nature of real graph datasets, approximate, rather than exact, graph matching is required. Furthermore, many modern applications need to query large graphs, each of which has hundreds to thousands of nodes and edges. TALE is an approximate subgraph matching tool for matching graph queries with a large number of nodes and edges. TALE employs a novel indexing technique that achieves a high pruning power and scales linearly with the database size.

Proper citation: Substructure Index-based Approximate Graph Alignment (RRID:SCR_003434) Copy   

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http://integrativemodeling.org/

An open source C++ and Python toolbox for solving complex modeling problems, and a number of applications for tackling some common problems in a user-friendly way. Its broad goal is to contribute to a comprehensive structural characterization of biomolecules ranging in size and complexity from small peptides to large macromolecular assemblies, by integrating data from diverse biochemical and biophysical experiments. It can also be used from the Chimera molecular modeling system, or via one of several web applications.

Proper citation: Integrative Modeling Platform (RRID:SCR_002982) Copy   

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http://www.nitrc.org/projects/ukftractography/

Software framework which uses an unscented Kalman filter for performing tractography. At each point on the fiber the most consistent direction is found as a mixture of previous estimates and of the local model. It is very easy to expand the framework and to implement new fiber representations for it. Currently it is possible to tract fibers using two different 1-, 2-, or 3-tensor methods. Both methods use a mixture of Gaussian tensors. One limits the diffusion ellipsoids to a cylindrical shape (the second and third eigenvalue are assumed to be identical) and the other one uses a full tensor representation. The project is written in C++. It could be used both as a Slicer3 module and as a standalone commandline application.

Proper citation: Diffusion Tractography with Kalman Filter (RRID:SCR_002585) Copy   

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http://www-lecb.ncifcrf.gov/NCISEM97/ncisem18.html

The Flicker image viewer is a Java applet which reads two images from the Internet and then displays them in the your Web browser. It allows you to enhance them in various ways and to compare them visually in a third window called the flicker window. The Open-source Flicker downloadable application is now available. The program uses the "flicker method" used in GELLAB with and with Xconf. The flicker method is the alternate display in the same visual space of two images being compared which are aligned by aligning similar morphologic features. Images may first be enhanced by spatial warping, pseudo 3-Dimensional projections, image sharpening, contrast enhancement and other transforms. The transformed images may then be presented using flickering. Flicker is a method for comparing images from different Internet sources on your Web browser. Scientists around the world often work on similar image data. More of this data is being published on the Internet each year. In the case of 2D protein electrophoretic gel images, maps identifying proteins in these gels are becoming increasingly available. Visually comparing 2D sample gels against these 2D gel database maps may suggest putative protein spot identification in many cases. Flicker was originally developed for comparing 2D protein gels across the Internet.

Proper citation: NCI Flicker Web Server. (RRID:SCR_003390) Copy   

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http://www.nitrc.org/projects/shape_mancova/

shapeAnalysisMANCOVA offers statistical shape analysis based on a parametric boundary description (SPHARM) as the point-based model computing method. The point-based models will be analyzed with the methods here proposed using multivariate analysis of covariance (MANCOVA). Here, the number of variates being tested is the dimensionality of our observations. Each point of these observations is a three dimensional displacement vector from the mean. The number of contrasts is the number of equations involved in the null-hypothesis. In order to encompass varying numbers of variates and contrasts, and to account for independent variables, a matrix computation is performed. This matrix represents the multidimensional aspects of the correlation significance and it can be transformed into a scalar measure by manipulation of its eigenvalues. Details of the methods can be found in its Insight Journal publication: http://hdl.handle.net/10380/3124

Proper citation: shapeAnalysisMANCOVA - SPHARM tools (RRID:SCR_002578) Copy   

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http://www.phe-culturecollections.org.uk/aboutus/index.jsp

Archival database of cell lines and microbial strains. Maintained by Public Health England, the database is used by scientists to determine the effects of various substances on human cells as well as for controls for diagnostic and antimicrobial susceptibility tests.

Proper citation: Health Protection Agency Culture Collections (RRID:SCR_002858) Copy   

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https://pydicom.github.io/

Software Python package for working with DICOM files, made for inspecting and modifying DICOM data in an easy pythonic way. The modifications can be written again to a new file. As a pure python package, it should run anywhere python runs without any other requirements.

Proper citation: pydicom (RRID:SCR_002573) Copy   

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http://www.egi.com/research-division-geodesic-system-components/eeg-software

A complete software package for working with electroencephalography (EEG) and event-related potential (ERP) data. You can acquire, review, analyze, and now ?see? your participant with synchronized video. Net Station also offers specialized tools and workflow options for both clinical and research applications, allows you to save different combinations of view settings (called workspaces) and helps with your reporting requirements by letting you set up and print custom cover pages. For more specialized work, Net Station also provides an optional electrical source estimation module (GeoSource) and an optional sensor location digitizer (Geodesic Photogrammetry System).

Proper citation: Net Station EEG Software (RRID:SCR_002453) Copy   

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http://www.genomeutwin.org/index.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Study of genetic and life-style risk factors associated with common diseases based on analysis of European twins. The population cohorts used in the Genomeutwin study consist of Danish, Finnish, Italian, Dutch, English, Australian and Swedish twins and the MORGAM population cohort. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterize the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide. The participating 8 twin cohorts form a collection of over 0.6 million pairs of twins. Tens of thousands of DNA samples with informed consents for genetic studies of common diseases have already been stored from these population-based twin cohorts. Studies targeted to cardiovascular traits are now being undertaken in MORGAM, a prospective case-cohort study. MORGAM cohorts include approximately 6000 individuals, drawn from population-based cohorts consisting of more than 80 000 participants who have donated DNA samples.

Proper citation: GenomEUtwin (RRID:SCR_002843) Copy   

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http://specimencentral.com/

World's open biospecimen research database where biobanks and biomedical researchers meet to exchange human biospecimen needs and supply: whole blood, serum, plasma, solid tissue samples and more. The connection is accelerated so researchers save valuable time and money and tissue banks utilize inventory. The pace of specimen procurement remains unacceptably slow to the biomedical research community. Specimen Central is the foremost global resource to aid biomedical researchers in expediting their search for high quality human biospecimens, tissues, samples and specimens. They facilitate your search for blood, whole blood, buccal swab, DNA, RNA, protein, cell lines, plasma, serum, RBC, white cells, buffy coat, fluid, marrow, urine, stem cells, and solid tissue such as tumor, tumor and biopsy materials spanning all manner of common and rare pathologies and indications including Alzheimer's, basal cell carcinoma, bladder cancer, bone cancer, brain cancer, breast cancer, cerebrospinal fluid, amniotic fluid, colorectal cancer, colon cancer, hodgkins and non-hodgkins lymphoma, kidney/renal cancer, leukemia, liver cancer, lung cancer, melanoma, multiple sclerosis, myeloma neuroblastoma, neurodegenerative diseases, ovarian cancer, pancreatic cancer, prostate cancer, urinary cancer. This includes adult and pediatric indications. Specimen Central users specify a number of variables in their Specimen Requests, including preparation, preservation and handling requirements such as cryo-preserved, FFPE (Formalin-fixed paraffin-embedded), formalin, frozen, refrigerated, OCT, snap frozen, paraffin block, fresh, prospective, autopsy or cadaveric, etc. Many users require clinically annotated date associated with their specimens, as well as documentation of IRB or ethics committee approval and informed consents. For Researchers Most specimen databases require researchers to waste time and effort entering lengthy registrations and search queries that yield poor results, if anything. Specimen Central solves this problem by having tissue banks search for you. From years to months, months to weeks, and weeks to days, Specimen Central seeks to reduce delays and costs in the research & development life cycle by expediting connections between demand and supply. For Biobanks The capital costs of maintaining a biobank infrastructure are substantial and growing. Biobanks use Specimen Central as a marketing tool to augment their business development efforts. By routinely checking Specimen Central's Specimen Requests, biobanks can uncover market demand for their inventories and develop new connections and revenue streams to defray costs. Specimen Central supplements - not displaces - the efforts of your sales representatives, agents, brokers and commercial partners.

Proper citation: SpecimenCentral.com (RRID:SCR_003536) Copy   

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http://www.geneticepi.com/Research/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 16,2023. Software application (entry from Genetic Analysis Software).

Proper citation: MILD (RRID:SCR_003335) Copy   

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http://cran.r-project.org/web/packages/enviPick/

Software for sequential partitioning, clustering and peak detection of centroided LC-MS mass spectrometry data (.mzXML). Interactive result and raw data plot.

Proper citation: enviPick (RRID:SCR_003059) Copy   

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http://www.nitrc.org/projects/segadapter/

An open source learning-based software that automatically learns how to transfer the output of a host segmentation tool closer to the user's manual segmentation using the image data and manual segmentation provided by the user. The motivation of this project is to bridge the gap between the segmentation tool developer and the tool users such that the existing segmentation tools can more effectively serve the community. More and more automatic segmentation tools are publicly available to today's researchers. However, when applied by their end-users, these segmentation tools usually can not achieve the performance that the tool developer reported. Discrepancies between the tool developer and its users in manual segmentation protocols and imaging modalities are the main reasons for such inconsistency.

Proper citation: Automatic Segmentation Tool Adapter (RRID:SCR_002481) Copy   

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http://www.nitrc.org/projects/pestica/

Software tool to detect physiologic signals from the data itself as well as an adaptive physiologic noise removal tool (Impulse Response Function or IRF-RETROICOR) that zooms in on noise with only 6 regressors, getting all the noise that 5th order RETROICOR gets. These tools will allow you to correct your data for physiologic noise with what you currently have. These signals are equivalent to a parallel monitored pulse signal and a respiratory chest-bellows signal. Do you have 3D+time EPI data (BOLD or perfusion) but no usable physio signals for pulse and respiration? Are you concerned about the effect of physio noise on your data but don't know what to do but regress data-derived signals that mix unknown functional signal with possible physio noise signal? Are you concerned about the number of regressors you're incorporating once you add 5th order RETROICOR (20 more regressors!)? This is for you.

Proper citation: PESTICA fMRI Physio Detection/Correction (RRID:SCR_002513) Copy   

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http://linkage.rockefeller.edu/pawe3d/

Software application (entry from Genetic Analysis Software)

Proper citation: PAWE-3D (RRID:SCR_003326) Copy   

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