Tools   Select Another Resource Report Type

http://www.gmu.edu/departments/krasnow/

The Krasnow Institute seeks to expand understanding of mind, brain, and intelligence by conducting research at the intersection of the separate fields of cognitive psychology, neurobiology, and the computer-driven study of artificial intelligence and complex adaptive systems. These separate disciplines increasingly overlap and promise progressively deeper insight into human thought processes. The Institute also examines how new insights from cognitive science research can be applied for human benefit in the areas of mental health, neurological disease, education, and computer design. It is this informed access to mind and brain that is the core of the mission of The Krasnow Institute. While their goals and tools are scientific, they also are fully cognizant of the applications of the results for the benefit of mankind, in areas like mental health, neurological diseases, and computer design. In asking the major questions they realized the necessity of being flexible, innovative, and trans-disciplinary. Therefore, they became dedicated to bringing together scholars from a wide variety of specialties and providing a milieu where they can be both productive and interactive. This institute will provide these researchers with the tools required to move ahead and create an environment of optimal scientific integrity coupling innovation with risk taking. The Krasnow institute is especially attuned to the deep insights from evolutionary biology, which is at the root of understanding all organismic functions including cognition; computer studies of complex systems, which present a revolution in our ability to deal with the world of interactive agents; and a long history of cognitive psychology, which provides a huge data base of human abilities and responses. It also continues to develop its long-term research program based on the contributions of George Mason University faculty holding joint appointments at Krasnow and other GMU academic departments. Additionally, the Krasnow Institute Department of Molecular Neuroscience, together with the College of Science (COS) and the College of Humanities and Social Sciences (CHSS), oversees the campus-wide Neuroscience Council in developing the Neuroscience PhD curriculum. Research groups in the Krasnow institute include: - Adaptive Systems Laboratory - Center for Neural Dynamics - Center for Social Complexity - Center for the Study of Neuroeconomics o Neuroeconomics Laboratory - Comparative Vertebrate Neurobiology Research Group - Center for Neuroinformatics, Neural Structures, and Neuroplasticity (CN3) o Computational and Experimental Neuroplasticity (CENlab) o Computational Neuroanatomy Group o Physiological and Behavioral Neuroscience in Juveniles (PBNJ) Lab - Receptor Complexes and Signaling Lab - Krasnow Investigations of Developmental Learning and Behavior (KIDLAB) - Neuro Imaging Core of the Krasnow Institute

Proper citation: George Mason University: Krasnow Institute for Advanced Study (RRID:SCR_001741) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.dreamhosters.com/?page_id=113#Genomic_Protein_Sequence_Analysis

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 10th,2023. An R software package for detecting and correcting biases in RNA-Sequencing data.

Proper citation: RNASeqBias (RRID:SCR_001739) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.med.yale.edu/group/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 10th,2023. An R code for Bayesian modeling of paired RNA-seq experiments.

Proper citation: pairedBayes (RRID:SCR_001738) Copy   

•   Source: SciCrunch Registry

https://www.hgsc.bcm.edu/content/sea-urchin-genome-project

Provides informationa about Genome of California Purple Sea Urchin, one species (Strongylocentrotus purpuratus) of which has been sequenced and annotated by Sea Urchin Genome Sequencing Consortium led by HGSC. Reports sequence and analysis of genome of sea urchin Strongylocentrotus purpuratus, a model for developmental and systems biology.

Proper citation: Sea Urchin Genome Project (RRID:SCR_001735) Copy   

•   Source: SciCrunch Registry

http://www.yahrparkinson.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 28, 2017. Foundation that helps junior physicians and neuroscientists continue their research on Parkinson's Disease and related disorders, with financial support for professional and intellectual development. It promotes an international community of researchers, focusing on the young enthusiastic investigators and clinicians who might otherwise be forced to abandon their ideas and efforts.

Proper citation: Melvin Yahr International Parkinson's Disease Foundation (RRID:SCR_001652) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/dnaclust/

Software program for clustering large number of short similar DNA sequences. It was originally designed for clustering targeted 16S rRNA pyrosequencing reads.

Proper citation: DNACLUST (RRID:SCR_001771) Copy   

•   Source: SciCrunch Registry

http://intermine.org/

An open source data warehouse system built for the integration and analysis of complex biological data that enables the creation of biological databases accessed by sophisticated web query tools. Parsers are provided for integrating data from many common biological data sources and formats, and there is a framework for adding data. InterMine includes a user-friendly web interface that works "out of the box" and can be easily customized for specific needs, as well as a powerful, scriptable web-service API to allow programmatic access to data.

Proper citation: InterMine (RRID:SCR_001772) Copy   

•   Source: SciCrunch Registry

http://ilyinlab.org/friend/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Friend is a bioinformatics application designed for simultaneous analysis and visualization of multiple structures and sequences of proteins and/or DNA/RNA. The application provides basic functionalities such as: structure visualization with different rendering and coloring, sequence alignment, and simple phylogeny analysis, along with a number of extended features to perform more complex analyses of sequence structure relationships, including: structural alignment of proteins, investigation of specific interaction motifs, studies of protein-protein and protein-DNA interactions, and protein super-families. Friend is also useful for the functional annotation of proteins, protein modeling, and protein folding studies. Friend provides three levels of usage; 1) an extensive GUI for a scientist with no programming experience, 2) a command line interface for scripting for a scientist with some programming experience, and 3) the ability to extend Friend with user written libraries for an experienced programmer. The application is linked and communicates with local and remote sequence and structure databases.

Proper citation: An Integrated Multiple Structure Visualization and Multiple Sequence Alignment Application (RRID:SCR_001646) Copy   

•   Source: SciCrunch Registry

http://www.intute.ac.uk/

Intute is a free online service that helps you to find the best web resources for your studies and research. It was created in response to users' needs and the changing Internet information environment. With millions of resources available on the Internet, it can be difficult to find useful material. The Intute subject specialists review and evaluate thousands of resources to help you choose the key websites in your subject. Intute can also help you develop your Internet research skills through our Virtual Training Suite tutorials, written by lecturers and librarians from universities across the UK. The discipline focus of their service is delivered through four new subject groups: * Science, Engineering and Technology (including geography) * Arts and Humanities * Social Sciences * Health and Life Sciences Intute is created by a consortium of seven universities, working together with a whole host of partners. The Intute consortium includes: * University of Birmingham * University of Bristol * Heriot-Watt University * The University of Manchester * Manchester Metropolitan University * University of Nottingham * University of Oxford Sponsors: Intute is funded by the Joint Information Systems Committee (JISC).

Proper citation: Intute: The Best Web Resources For Education and Research (RRID:SCR_001764) Copy   

•   Source: SciCrunch Registry

http://protein.bio.unipd.it/pasta2/

Online interface that utilizes an algorithm to predict the most aggregation-prone portions and the corresponding beta-strand inter-molecular pairing for a given input sequence. Users can paste the sequence into the interface and output the appropriate sequence.

Proper citation: Prediction of Amyloid Structure Aggregation (RRID:SCR_001768) Copy   

•   Source: SciCrunch Registry

https://www.uniklinik-freiburg.de/mr-en/research-groups/diffperf/fibertools.html

Implemented under MATLAB, this DTI image processing toolbox provides import-filters for several MR file standards, a processing unit to calculate the diffusion tensors; several GUI based tools to calculate fiber tracks and to evaluate the DTI dataset. The results can be filed as images with 3D impression or can be logged in formatted ASCII files. Tools and features: * DTI Processing Unit: Calculates the diffusion tensors and their eigenvalues and eigenvectors. Different file formats are supported (like DICOM, Bruker, binary files, Matlab structures). The standard SIEMENS and GE diffusion encoding schemes are supported; other schemes have to be defined in a separate text, .m or .mat file. * FiberTracking: ** Fiber tracking is realized by using the FACT algorithm (Mori et al., Annal. Neurol 1999). ** Probabilistic tracking realized by using the PiCo (Parker et al., JMRI 2003) approach but with DTI data as basis. It is possible to extract pathways between two seeds by combining two maps (Kreher et al., NeuroImage 2008). ** Global Fiber Tracking on basis of HARDI or DTI data. The method is based on the approach reported in (Marco Reisert et al: Global fiber reconstruction becomes practical. NeuroImage 54(2):955-62) * FiberViewer: ** Visualization and Navigation through different data modalities like DTI maps, fiber tracks, diffusion main directions. ** Supports different kinds of DTI maps (e.g. FA, Trace, lambda images ) ** Creation and manipulation of mask based ROIs. ** Selection of streamline fibers ** Visualization of probabilistic fiber tracking results ** Documentation by logging statistics of ROIs and fiber tracks into text files. ** Import/Export from/to ANALYZE or Nifti * 3D Visualizer: Visualization of map slices, ROIs, and fiber tracks with 3D impression. * Batch Editor: Automatic processing of high amounts of data. Possibility to link processing with SPM8 easily.

Proper citation: DTI and Fibertools Software Package (RRID:SCR_001641) Copy   

•   Source: SciCrunch Registry

http://www.bioit.org.cn/ao/aobase

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. AOBase is a database for antisense oligonucleotides (AOs) selection and design. AOBase is a database developed to facilitate Antisense Oligonucleotides (ODNs) selection for gene expression modulation and to provide a free data source for computer aided ODNs design. Information about valid and invalid ODNs reported in literature are collected and stored in the database, including oligo sequences, target sequences, secondary structures of the target sites, oligo activity measured, and the assay type used for activity measurement. The details on target RNA molecules and reference literature can be explored through the hyperlinks linked to GenBank and PubMed respectively. Each record can be searched for via two web retrieval interfaces: 1) TargetSearch interface, which allows users to query ODNs by name, accession number, or only imprecise descriptions of its target RNA; 2) AOSearch interface, which allows users to search ODNs with several parameters combined, such as oligo activity measured, oligo concentration applied, and motifs involved in oligo sequences. With these two retrieval interfaces, AOBase can be used to select effective ODNs for gene function exploration without expensive in vitro screening experiments, and contribute to mining rules for rational ODNs design. A user friendly interface to encourage data submission is provided.

Proper citation: Database for Antisense Oligonucleotides Selection and Design (RRID:SCR_001753) Copy   

•   Source: SciCrunch Registry

Issue

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

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

Proper citation: PLINK (RRID:SCR_001757) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/nidag

An international working group dedicated to improving access to neuroimaging results in a free and open-access manner. It seeks to establish a universal coordinate database, including both past papers and future studies. Their current project involves the creation of a comprehensive database of neuroimaging results searchable based on standardized coordinates. Once complete, this will allow anyone to find all of the articles that report a coordinate, or set of coordinates, easily and without cost. Eventually, they hope to expand this database to include not only coordinates, but statistical parametric maps as well. Formation of such a database will increase the likelihood of relevant papers being found and cited, and also be a very useful tool for those interested in meta-analysis, and hopefully clarify structure-function relationships. They are interested in hearing from people who might be willing to contribute to their projects, particularly those with programming experience. The number of published neuroimaging studies is increasing rapidly and it is not feasible to read them all. If a computer database could store key information from published fMRI papers and make that information easier to search or share, this would have substantial benefits for the neuroimaging community. Projects like AMAT, Brainmap, Brede and SumsDB have started to tackle this problem. NIDAG wants to formalize and improve these databases so that they meet the needs of the neuroimaging community. Formal meta-analysis of published data is a valuable way to assess the consistency and reliability of experimental results. A database of neuroimaging results would facilitate meta-analyses, in conjunction with tools like GingerALE and Multi-level Kernel Density Analysis.

Proper citation: NIDAG: Neuroimaging Data Access Group (RRID:SCR_001674) Copy   

•   Source: SciCrunch Registry

http://www.atcc.org/

Global nonprofit biological resource center (BRC) and research organization that provides biological products, technical services and educational programs to private industry, government and academic organizations. Its mission is to acquire, authenticate, preserve, develop and distribute biological materials, information, technology, intellectual property and standards for the advancement and application of scientific knowledge. The primary purpose of ATCC is to use its resources and experience as a BRC to become the world leader in standard biological reference materials management, intellectual property resource management and translational research as applied to biomaterial development, standardization and certification. ATCC characterizes cell lines, bacteria, viruses, fungi and protozoa, as well as develops and evaluates assays and techniques for validating research resources and preserving and distributing biological materials to the public and private sector research communities.

Proper citation: ATCC (RRID:SCR_001672) Copy   

•   Source: SciCrunch Registry

http://www.depressionalliance.org/

DA works to relieve and to prevent depression by providing information and support services to those who are affected by it via their publications, supporter services and network of self-help groups for people affected by depression. Depression Alliances services help people to understand, work with and recover from symptoms associated with depression. Depression Alliance believes that the stigma and lack of accurate information surrounding depression continues to prevent people from seeking and finding appropriate and vital help when it is required. Early intervention and information are crucial in enabling those affected by depression to recover quickly and critically in preventing further episodes. Informed by the experiences of people with depression and by research, DA works extensively with government agencies and healthcare professionals to improve the service provision for those affected by depression. DA also campaigns to raise awareness amongst the general public about the realities of this severe and enduring illness by organizing a variety of events and initiatives.

Proper citation: Depression Alliance (RRID:SCR_001709) Copy   

•   Source: SciCrunch Registry

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

Software package that implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.

Proper citation: unifiedWMWqPCR (RRID:SCR_001706) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.13/bioc/html/cqn.html

A normalization tool for RNA-Seq data, implementing the conditional quantile normalization method.

Proper citation: CQN (RRID:SCR_001786) Copy   

•   Source: SciCrunch Registry

https://github.com/sbotond/rlsim

Software package for simulating RNA-seq library preparation with parameter estimation.

Proper citation: rlsim (RRID:SCR_001703) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/src/contrib/Archive/PoissonSeq/

Software package that implements a method for normalization, testing, and false discovery rate estimation for RNA-sequencing data.

Proper citation: PoissonSeq (RRID:SCR_001784) Copy   

•   Source: SciCrunch Registry