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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   

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https://ecl.earthchem.org/view.php?id=329

Database contating hydrothermal spring geochemistry that hosts and serves the full range of compositional data acquired on seafloor hydrothermal vents from all tectonic settings. It can accommodate published historical data as well as legacy and new data that investigators contribute.

Proper citation: VentDB (RRID:SCR_001632) Copy   

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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   

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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   

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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   

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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   

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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   

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http://start.sampleofscience.com

THIS RESOURCE IS NO LONGER IN SERVICE.

Free access service resource dedicated to connect researchers creating scientific samples with scientists who need samples for their experiments. With Sample of Science researchers can submit samples, or contact scientists proposing sample for dissemination. Each disseminated sample also gets its description published in Sample of Science Bulletin, a dedicated open access journal. It acquires a Digital Object Identifier (DOI) and becomes a fully citable item. Because both adequate sample descriptions and mutually-agreed dissemination conditions are key factors for a fruitful dissemination that respects mutual interest, Sample of Science provides tools to elaborate, communicate, discuss, and refine both sample description and dissemination conditions. This process, termed peer-adoption process, results in the publication of disseminated sample descriptions in Sample of Science Bulletin, a dedicated open access publication. The publication in Sample of Science Bulletin is useful to provide adequate recognition to Sample Authors who contribute to the development of science by offering visibility to their disseminated samples. To the adopter it provides experimental details regarding the sample under the form of a citable reference useful for any future publications involving this sample. To a larger scientific community interested in material science, it provides a useful tool to stay abreast the activity of sample providers in their respective field of expertise.

Proper citation: Sample of Science (RRID:SCR_001656) Copy   

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http://www.salk.edu/labs/slesinger/index.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This lab is investigating the molecular details of how potassium ion channels open and close (i.e. gating), the cellular regulation of potassium channels in nerve cells, and more recently, their role in drug addiction and mental disorders. There are currently two related areas of focus in the lab. One main area of research is investigating the G protein regulation of GIRK channels, utilizing structural, biochemical and electrophysiological strategies. The other area extends from the G protein regulation experiments to studies that examine the role of GIRK channels in the neural response to drugs of abuse, utilizing biochemical, electrophysiological and behavioral strategies.

Proper citation: Salk Institute for Biological Studies - Slesinger Lab (RRID:SCR_001850) Copy   

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http://www.genabel.org/packages/GenABEL

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. R software library for genome-wide association analysis for quantitative, binary and time-till-event traits.

Proper citation: GenABEL (RRID:SCR_001842) Copy   

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http://surfer.nmr.mgh.harvard.edu/

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

Proper citation: FreeSurfer (RRID:SCR_001847) Copy   

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http://silac.org/

Stable isotope labeling with amino acids in cell culture (SILAC) is a simple and straightforward approach for in vivo incorporation of a label into proteins for mass spectrometry (MS)-based quantitative proteomics. SILAC relies on metabolic incorporation of a given "light" or "heavy" form of the amino acid into the proteins. The method relies on the incorporation of amino acids with substituted stable isotopic nuclei (e.g. deuterium, 13C, 15N). In an experiment, two cell populations are grown in culture media that are identical except that one of them contains a "light" and the other a "heavy" form of a particular amino acid (e.g. 12C and 13C labeled L-lysine, respectively). When the labeled analog of an amino acid is supplied to cells in culture instead of the natural amino acid, it is incorporated into all newly synthesized proteins. After a number of cell divisions, each instance of this particular amino acid will be replaced by its isotope labeled analog. Since there is hardly any chemical difference between the labeled amino acid and the natural amino acid isotopes, the cells behave exactly like the control cell population grown in the presence of normal amino acid. It is efficient and reproducible as the incorporation of the isotope label is 100%. SILAC Applications: - Differential expression of proteins and identification of disease biomarkers - Cell signaling dynamics - Analysis of yeast pheromone signaling pathway - Identification of methylation sites - Identification of protease substrates - Study of protein complexes/protein interactions - Analysis of signaling pathways and effect of pharmacological inhibitors - Subcellular proteomics Sponsors: Supported in part by an NIH Roadmap grant Technology Center for Networks & Pathways of Lysine Modification.

Proper citation: Stable Isotope Labeling with Amino Acids in Cell Culture (RRID:SCR_001873) Copy   

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https://urgi.versailles.inra.fr/Tools/S-Mart

Software toolbox that manages your RNA-Seq and ChIP-Seq data and also produces many different plots to visualize your data. It performs several tasks that are usually required during the analysis of mapped RNA-Seq and ChIP-Seq reads, including data selection and data visualization. It includes the selection (or the exclusion) of the data that overlaps with a reference set, clustering and comparative analysis. It also provides many ways to visualize data: size of the reads, density on the genome, distance with respect to a reference set, and the correlation of two data sets (with cloud plots). A computer science background is not required to run it through a graphical interface and it can be run on any personal computer, yielding results within an hour for most queries.

Proper citation: S-MART (RRID:SCR_001908) Copy   

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http://www.dendrites.org/software

Dendritica is a program package for relating dendritic geometry and signal propagation. The programs are based on those used for the simulations described in the following paper: Vetter, P., Roth, A. & Husser, M. (2001). Action potential propagation in dendrites depends on dendritic morphology. Journal of Neurophysiology, 85: 926-937. Dendritica can functionally be divided into three main parts: - Interactive morphological analysis and electrophysiological simulation of single cells - Automated batch simulations across a set of morphologies using the same simulation parameters - Automated analysis of batch simulation runs Dendritica requires NEURON 4.1.1 with some modifications described in Appendix 1. It was tested for NEURON 4.1.1 on Linux and SGI IRIX. Some modifications to the Dendritica code may be necessary in order to run it on older or newer versions of NEURON. Sponsors: This work was supported by the Wellcome Trust, the European Community, the Max-Planck-Gesellschaft, the Wellcome Trust 4-year PhD Programme in Neuroscience.

Proper citation: Dendritica: Software Tools for Studying Dendritic Signaling (RRID:SCR_001865) Copy   

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https://medicine.stonybrookmedicine.edu/pathology/neuropathology

This is a primer of basic neuropathology- The Central Nervous System and Skeletal Muscle. It is organized in chapters by category of disease with a separate chapter for skeletal muscle. Many of the diseases could be included in more than one chapter because of overlapping pathophysiology; in each case the disorder is included in a single section in the interest of convenience. In order to recognize pathology one must have a basic foundation in normal structure, so the first chapter is an overview of basic regional central nervous system structure and anatomy. It includes an introduction to neurohistology. Other chapters address the pathophysiology of different categories of disease and provide examples of gross and microscopic pathology when they are available.

Proper citation: Stony Brook University Medical Center: Neuropathology Primer (RRID:SCR_001866) Copy   

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http://dendrites.esam.northwestern.edu/

This database contains morphologies of hippocampal pyramidal cells and interneurons (in Neurolucida, NEURON, and pdf formats) as well as data recorded from those cells. Sponsors:This work was supported by grants from the NIH (T32-GM-08061 to T.J.M., F32-NS-10532 to N.L.G., and R01-NS35180 and R01-NS 46064 to N.S. and W.L.K.) and NSF (IGERT fellowship to Y.K.). NS46064 is part of the NSF/NIH Collaborative Research in Computational Neuroscience Program

Proper citation: SPRUSTON / KATH LAB: Neuraling Modeling Database NEURAL MODELING DATABASE (RRID:SCR_001869) Copy   

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http://www.kaist.edu/html/en/index.html

Institute dedicated to research in science and technology in South Korea modeled after a research university.

Proper citation: Korea Advanced Institute of Science and Technology; Daejeon; South Korea (RRID:SCR_001902) Copy   

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http://www.sanbi.ac.za/resources/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. The South African National Bioinformatics Institute delivers biomedical discovery appropriate to both international and African context. Researchers at SANBI perform the highest level of research and provide excellence in education. Research at SANBI has set well recognized milestones in the field of computational biology. The tools and techniques used have not only been developed but also implemented across heterogeneous domains of advanced research. Local and international efforts have driven our discoveries. Until recently, the core of SANBIs research has focused upon gene expression biology. Methods developed and applied at SANBI revolve around a greater understanding of the underlying causes of diseases. SANBI approaches the problem by comparison of genes, genomes and transcriptomes. It uses computational gene expression biology to create novel biological insights and to provide biomarkers for experimental validation. It also performs analysis of human genome variation, transcriptional diversity on both the expression and splicing level and the unravelling of transcriptional regulatory networks. Resources - Hinv, STACKdb, Malaria resources and Trypanosome databases are available for on-line seaching. - SANBI offers WCD, STACKdb, stackPACK and eVOC and the eVOKE viewer as tools that can be downloaded. Sponsors: SANBI receives funding and support from a range of organisations in South Africa and Internationally. Organisations currently supporting SANBI include: South Africa * South African Medical Research Council * South African AIDS Vaccine Initiative * National Bioinformatics Network * National Research Foundation * Claude Leon Foundation * International Business Machines Inc. Europe * European Unions 6th Framework Programme * World Health Organization USA * US National Institutes of Health * Fogarty International Centre * Ludwig Institute for Cancer Research

Proper citation: South African National Bioinformatics Institute: Resources (RRID:SCR_001867) Copy   

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http://www.blki.hu/~szucs/OS3.html

Orbital Spike is a tool for time series analysis. It contains a wide range of methods to analyze data from point processes such as spike arrival times, heart beats or other behavioral episodes. It is optimized this program for spike trains but it works with other types of data, too. The program can analyze up to 8 channels recorded simultaneously each containing a maximum of 132,000 events (spikes). Assuming an average firing rate of 10 Hz for a neuron, you can then analyze a time series of approximately 3 and half hours long. There are up to 8 panels shown in the Orbital Spike desktop. The panels will contain the kind of data of interest. The graphs are associated with a bunch of parameters like window width, bin size, resolution, delay etc. All these parameters are listed in the parameter box, which appears on the right side of the desktop. It is pretty easy to change the parameters and what is nice, the corresponding graph(s) will be recalculated immediately. You can also use a dialog box to change parameters. There are a lot of functions, statistics, graphs and diagrams available. A few of them are: * Interspike interval sequences * ISI Poincar * maps or return maps Instantaneous firing rate * ISI histograms and probability densities * Joint ISI and MSI probability densitograms * Autocorrelation, crosscorrelation * Spike density functions using kernel estimators * Fourier-amplitude spectrum and spectogram * Symbolic maps, recurrence plots * Phase plots of spike density functions Sponsors: Support for this work came from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Engineering and Geosciences, under Grants DE-FG03-90ER14138 and DE-FG03-96ER14592; from the Office of Naval Research under Grant N00014-00-1-0181; from the National Science Foundation under Grant PHY0097134; from the National Institutes of Health under Grants R01 NS-40110-01A2 and 1RO1 NS-40110; and from the Army Research Office under Contract DAAD19-01-1-0026. R. D. Pinto was supported by the State of Sao Paulo Research Foundation (FAPESP).

Proper citation: Spike Train Analysis Software by Attila Szucs: Orbital Spike 4 (RRID:SCR_001868) Copy   

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http://www.sdcms.org/

The San Diego County Medical Society (SDCMS) is a non-profit organization designed to address San Diego healthcare needs for all patients and physicians through innovation, education and service. The SDCMS Foundation is advancing several innovative programs and initiatives: - The Emergency Department Medical Home (EDMH) Project matches uninsured patients in the emergency department with public and private medical coverage and establishes a medical home for them at local community health centers. - Project Access San Diego (PASD) is a program that connects eligible, low-income, uninsured patients with physicians who provide deeply discounted or pro bono care. - The SDCMS Foundation has also established five medical student scholarships at the UCSD School of Medicine.

Proper citation: San Diego County Medical Society (RRID:SCR_001854) Copy   

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