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http://www.cognitiveatlas.org/

Knowledge base (or ontology) that characterizes the state of current thought in cognitive science that captures knowledge from users with expertise in psychology, cognitive science, and neuroscience. There are two basic kinds of knowledge in the knowledge base. Terms provide definitions and properties for individual concepts and tasks. Assertions describe relations between terms in the same way that a sentence describes relations between parts of speech. The goal is to develop a knowledge base that will support annotation of data in databases, as well as supporting improved discourse in the community. It is open to all interested researchers. A fundamental feature of the knowledge base is the desire and ability to capture not just agreement but also disagreement regarding definitions and assertions. Thus, if you see a definition or assertion that you disagree with, then you can assert and describe your disagreement. The project is led by Russell Poldrack, Professor of Psychology and Neurobiology at the University of Texas at Austin in collaboration with the UCLA Center for Computational Biology (A. Toga, PI) and UCLA Consortium for Neuropsychiatric Phenomics (R. Bilder, PI). Most tasks used in cognitive psychology research are not identical across different laboratories or even within the same laboratory over time. A major advantage of anchoring cognitive ontologies to the measurement level is that the strategy for determining changes in task properties is easier than tracking changes in concept definitions and usage. The process is easier because task parameters are usually (if not always) operationalized objectively, offering a clear basis to judge divergence in methods. The process is also easier because most tasks are based on prior tasks, and thus can more readily be considered descendants in a phylogenetic sense.

Proper citation: Cognitive Atlas (RRID:SCR_002793) Copy   

•   Source: SciCrunch Registry

http://diseasome.eu

A disease / disorder relationships explorer and a sample of a map-oriented scientific work. It uses the Human Disease Network dataset and allows intuitive knowledge discovery by mapping its complexity. The Human Disease Network (official) dataset, a poster of the data and related book (Biology - The digital era, ISBN: 978-2-271-06779-1) are available. This kind of data has a network-like organization, and relations between elements are at least as important as the elements themselves. More data could be integrated to this prototype and could eventually bring closer phenotype and genotype. Results should be visual, but also printable. Creating posters can enhance collaborative work. It facilitates discussion and sharing of ideas about the data. This website initiative is an invitation to think about the benefits of networks exploration but above all it tries to outline future designs of scientific information systems.

Proper citation: Diseasome (RRID:SCR_002792) Copy   

•   Source: SciCrunch Registry

http://andestools.sourceforge.net/

Software library and a suite of applications, written in Perl and R, for deep sequencing statistical analyses.

Proper citation: ANDES (RRID:SCR_002791) Copy   

•   Source: SciCrunch Registry

https://rnaidesigner.lifetechnologies.com/rnaiexpress/

A free tool to design effective RNAi molecules that includes the following target design options: Stealth RNAi siRNA, siRNA, miR RNAi, shRNA, siRNA to Stealth RNAi siRNA, and siRNA to shRNA.

Proper citation: BLOCK-iT RNAi Designer (RRID:SCR_002794) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/gap

Database developed to archive and distribute clinical data and results from studies that have investigated interaction of genotype and phenotype in humans. Database to archive and distribute results of studies including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits.

Proper citation: NCBI database of Genotypes and Phenotypes (dbGap) (RRID:SCR_002709) Copy   

•   Source: SciCrunch Registry

http://www.perkinelmer.com/pages/020/cellularimaging/products/volocity.xhtml

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. 3D image analysis software to visualize, analyze and validate 3D fluorescence images from a wide range of confocal microscopy, widefield and high content screening systems. It is fully integrated for a seamless user experience.

Proper citation: Volocity 3D Image Analysis Software (RRID:SCR_002668) Copy   

•   Source: SciCrunch Registry

http://uwaging.org/genesdb/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 17,2023. A database of genes and interventions connected with aging phenotypes including those with respect to their effects on life-span or age-related neurological diseases. Information includes: organism, aging phenotype, allele type, strain, gene function, phenotypes, mutant, and homologs. If you know of published data (or your own unpublished data that you'd like to share) not currently in the database, please use the Submit a Gene/Intervention link.

Proper citation: Aging Genes and Interventions Database (RRID:SCR_002701) Copy   

•   Source: SciCrunch Registry

http://www.dana.org

A private philanthropy with principal interests in brain science, immunology, and education. The portal provides general information about the brain and current brain research, links to validated sites related brain disorders, education resources and lesson plans, and support for the training of in-school arts specialists. The Dana Foundation science and health grants support brain research in neuroscience and immunology and their interrelationship in human health and disease. The grant sections include brain and immuno-imaging, clinical neuroscience research, human immunology and neuroimmunology. The Foundation also occasionally sponsors workshops and forums for working scientists, as well as offering funding for selected young researchers to continue their education or to attend seminars and workshops elsewhere.

Proper citation: Dana Foundation (RRID:SCR_002789) Copy   

•   Source: SciCrunch Registry

http://www.neuroscience-berlin.de/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 10, 2017. In the last few years the Berlin neuroscience community has been highly successful in creating new research projects. Not the least of these is the cluster of excellence, NeuroCure, which has brought nine new professors and their research groups to Berlin. Along with the increasing levels of research, a number of new neuroscience training programs have recently been established. In 2002 the International Graduate Program Medical Neurosciences was the only structured Masters and PhD program: as of 2009 Berlin hosts four neuroscience schools and several DFG funded research training groups. The purpose of this website to highlight the many projects and people involved in the Berlin neuroscience community. We hope that you, the reader, can benefit from this summary., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Neuroscience Berlin (RRID:SCR_002741) Copy   

•   Source: SciCrunch Registry

http://www.unibas.ch/

Public university in Basel, Switzerland that offers degree programs in theology, law, medicine, humanities and social sciences, science, psychology, and business and economics.

Proper citation: University of Basel; Basel; Switzerland (RRID:SCR_002699) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/pathview.html

A tool set for pathway-based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.

Proper citation: Pathview (RRID:SCR_002732) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/glprobs/

Software implementing a simple and effective approach to improve the accuracy of multiple sequence alignment.

Proper citation: GLProbs (RRID:SCR_002739) Copy   

•   Source: SciCrunch Registry

http://www.neuro.nl

The department of Neuroscience was founded in 2001, resulting from a merger between the Physiology and Anatomy department. In 2008, the BNT department joined forces. At present we consist of about 150 people. Our research is dedicated to Plasticity and Dynamics of Sensori-Motor Systems, which we investigate at the physiological, anatomical end molecular level in 18 different research groups. We have teaching responsibilities within the whole bachelor's phase of the medical curriculum at the Erasmus MC, teaching both basic anatomy and physiology, as well as neuroscience. The department hosts its own Master of Neuroscience program. The department of Neuroscience is embedded in the ONWAR, Helmholtz, and MGC research school

Proper citation: Erasmus MC Department of Neuroscience (RRID:SCR_002737) Copy   

•   Source: SciCrunch Registry

http://www.flymine.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Integrated database of genomic, expression and protein data for Drosophila, Anopheles, C. elegans and other organisms. You can run flexible queries, export results and analyze lists of data. FlyMine presents data in categories, with each providing information on a particular type of data (for example Gene Expression or Protein Interactions). Template queries, as well as the QueryBuilder itself, allow you to perform searches that span data from more than one category. Advanced users can use a flexible query interface to construct their own data mining queries across the multiple integrated data sources, to modify existing template queries or to create your own template queries. Access our FlyMine data via our Application Programming Interface (API). We provide client libraries in the following languages: Perl, Python, Ruby and & Java API

Proper citation: FlyMine (RRID:SCR_002694) Copy   

•   Source: SciCrunch Registry

http://www.wolframalpha.com/

Wolfram Alpha is a computational knowledge engine that to make all systematic knowledge computable. Although, this is not a specific neuroscience related resource, the computational and math element will be helpful. Wolfram Alpha's long-term goal is to make all systematic knowledge immediately computable and accessible to everyone. It aims to collect and curate all objective data; implement every known model, method, and algorithm; and make it possible to compute whatever can be computed about anything. It's goal is to build on the achievements of science and other systematizations of knowledge to provide a single source that can be relied on by everyone for definitive answers to factual queries. Wolfram Alpha aims to also bring expert-level knowledge and capabilities to the broadest possible range of peoplespanning all professions and education levels. It's goal is to accept completely free-form input, and to serve as a knowledge engine that generates powerful results and presents them with maximum clarity. Lastly, Wolfram Alpha is an ambitious, long-term intellectual endeavor that it intends to deliver increasing capabilities over the years and decades to come. With a world-class team and participation from top outside experts in countless fields, it's goal is to create something that will stand as a major milestone of 21st century intellectual achievement. As of now, Wolfram Alpha contains 10+ trillion pieces of data, 50,000+ types of algorithms and models, and linguistic capabilities for 1000+ domains. Built with Mathematicawhich is itself the result of more than 20 years of development at Wolfram ResearchWolfram Alpha's core code base now exceeds 5 million lines of symbolic Mathematica code. Running on supercomputer-class compute clusters, Wolfram Alpha makes extensive use of the latest generation of web and parallel computing technologies, including webMathematica and gridMathematica. Its knowledge base and capabilities already span a great many domains, and its underlying framework has the power and flexibility to support ready extension to essentially any domain that is based on systematic knowledge.

Proper citation: Wolfram Alpha Computational Knowledge Engine (RRID:SCR_002693) Copy   

•   Source: SciCrunch Registry

http://cbb.sjtu.edu.cn/~ccwei/pub/software/CTF/CTF.php

Conditional random field (CRF) based transcription factor binding site (TFBS) finding system. The underlying CRF model can integrate features of different sources.

Proper citation: CTF (RRID:SCR_002692) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.charite.de/superpred/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on November 24,2025. Publicly available web-server to predict medical indication areas based on properties and similarity of chemical compounds. The web-server translates a user-defined molecule into a structural fingerprint that is compared to about 6300 drugs, which are enriched by 7300 links to molecular targets of the drugs, derived through text mining followed by manual curation. Links to the affected pathways are provided. The similarity to the medical compounds is expressed by the Tanimoto coefficient that gives the structural similarity of two compounds. A similarity score higher than 0.85 results in correct ATC prediction for 81% of all cases. As the biological effect is well predictable, if the structural similarity is sufficient, the web-server allows prognoses about the medical indication area of novel compounds and to find new leads for known targets. The combination of physicochemical property and similarity searching provides the possibility to detect new biologically active compounds and novel targets for drug-like compounds. SuperPred can be applied for drug repositioning purposes, too. A further intention of SuperPred is to find side effects elicited by drugs caused through off-target hits.

Proper citation: SuperPred: Drug classification and target prediction (RRID:SCR_002691) Copy   

•   Source: SciCrunch Registry

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

Java library used for the execution of discrete Fourier transforms in 1-D, 2-D and 3-D through the implementation of Fast Fourier Transform (FFT) algorithms. * The FFT library has been written in Java for portability across different platforms, integrated into a single jar file for easy implementation. * The FFT library provides forward and backward fast Fourier transforms in 1-D, 2-D and 3-D with an easy-to-use manner. * The FFT requires the length equal to a number with an integer power of two. This library automatically examines the input data and detects the length to prevent improper execution.

Proper citation: FFT Library (RRID:SCR_002698) Copy   

•   Source: SciCrunch Registry

http://www.LONI.usc.edu/Software/ShapeViewer

Java-based geometry viewer that supports file formats used by Center for Computational Biology (CCB) researchers and provides necessary viewing functions. ShapeViewer uses ShapeTools library support to read and display LONI Ucf, VTX XML, FreeSurfer, Minc Obj (both binary and ascii), Open Dx, Gifti, and OFF format data files.

Proper citation: LONI ShapeViewer (RRID:SCR_002695) Copy   

•   Source: SciCrunch Registry

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

A Java-based visualization and analysis application that can process 2D and 3D image files and provides convenient methods for users to overlay multiple datasets. * Simultaneous visualization of multiple image volumes. * Tools for labeling and masking of structures. * Framework for the Mouse Atlas Project.

Proper citation: Synchronized Histological Image Viewing Architecture (RRID:SCR_002690) Copy   

•   Source: SciCrunch Registry