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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.farsight-toolkit.org/wiki/FARSIGHT_Toolkit

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. A collection of software modules for image data handling, pre-processing, segmentation, inspection, editing, post-processing, and secondary analysis. These modules can be scripted to accomplish a variety of automated image analysis tasks. All of the modules are written in accordance with software practices of the Insight Toolkit Community. Importantly, all modules are accessible through the Python scripting language which allows users to create scripts to accomplish sophisticated associative image analysis tasks over multi-dimensional microscopy image data. This language works on most computing platforms, providing a high degree of platform independence. Another important design principle is the use of standardized XML file formats for data interchange between modules.

Proper citation: Farsight Toolkit (RRID:SCR_001728) Copy   

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http://cmb.gis.a-star.edu.sg/ChIPSeq/paperCCAT.htm

THIS RESOURCE IS OUT OF SERVICE, documented on April 5, 2017, A software package for the analysis of ChIP-seq data with negative control., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CCAT (RRID:SCR_001843) Copy   

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http://www.bioconductor.org/packages/devel/bioc/html/CNVrd2.html

A software package that uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions.

Proper citation: CNVrd2 (RRID:SCR_001723) 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://talasso.cnb.csic.es/

Tool for quantification of human miRNA-mRNA Interactions. TaLasso is also available as Matlab or R code.

Proper citation: TaLasso (RRID:SCR_001726) 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://compbio.iupui.edu/group/6/pages/alteventfinder

Software tool for deriving data-driven alternative splicing (AS) events from RNA-seq data. It analyses the transcripts built by Cufflinks or Scripture and outputs AS event annotations which is compatible with MISO. It can be used for annotating novel AS events from a well-annotated species such as human. It can also be used for species of which known AS event annotation is not available. The current release (v0.1) supports skipped exon events only.

Proper citation: Alt Event Finder (RRID:SCR_001846) Copy   

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http://bioconductor.org/packages/2.13/bioc/html/sSeq.html

Software package to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution.

Proper citation: sSeq (RRID:SCR_001719) Copy   

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http://dial.mc.duke.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The Duke Image Analysis Laboratory (DIAL) is committed to providing comprehensive imaging support in research studies and clinical trials to various agencies. The capabilities of the lab include protocol development, site training and certification, and image archival and analysis for a variety of modalities including magnetic resonance imaging, magnetic resonance spectroscopy, computed tomography and nuclear medicine. DIAL uses the latest technologies to analyze Magnetic Resonance Imaging (MRI) data sets of the brain. Currently the lab is engaged in measurement of the hippocampus, amygdala, caudate, ventricular system, and other brain regional volumes. Each of these techniques have undergone a rigorous validation process. The measurements of brain structures provide a useful means of non-invasively testing for changes in the brain of the patient. Changes over time in the brain can be detected, and evaluated with respect to the treatment that the patient is receiving. Magnetic Resonance Spectroscopy (MRS) allows DIAL to obtain an accurate profile of the chemical content of the brain. This sensitive technique can detect small changes in the metabolic state of the brain; changes that vary in response to administration of therapeutic agents. The ability to detect these subtle shifts in brain chemistry allows DIAL to identify changes in the brain with more sensitivity than allowed by image analysis. In this respect, NMR spectroscopy can provide early detection of changes in the brain, and serves to compliment the data obtained from image analysis. Additionally, DIAL also contains SQUID (Scalable Query Utility and Image Database). It is an image management system developed to facilitate image management in research and clinical trials: SQUID offers secure, redundant image storage and organizational functions for sorting and searching digital images for a variety of modalities including MRI, MRS, CAT Scan, X-Ray and Nuclear Medicine. SQUID can access images directly from DUMC scanners. Data can also be loaded via DICOM CDs, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Duke University Medical Center: Duke Image Analysis Laboratory (RRID:SCR_001716) 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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http://www.kcl.ac.uk/index.aspx

Public research university located in London, United Kingdom that offers undergraduate, graduate, and professional degree programs in medicine, economics, social sciences, etc.

Proper citation: King's College London; London; United Kingdom (RRID:SCR_001744) 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://web.archive.org/web/20121114105735/https://histo.life.illinois.edu/histo/atlas/index.php

This portal leads to the Internet Atlas of Histology. This atlas allows you to explore the complete set of histological specimens that features many excellent plastic sections prepared by Aulikki Kokko-Cunningham, M.D. Also called University of Illnois at Urbana-Champaign, the College of Medicine: Internet Atlas of Histology Over 1000 labeled histological features are labeled and have accompanying functional descriptions. All of this information is accessible though an alphabetical index and a search engine. This resource has images categorized in: - Slides: Links to all of the specimens - Objects:Index of histological features Sponsors: This resource is supported by UIUC.

Proper citation: Internet Atlas of Histology (RRID:SCR_001745) 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://www.animalgenome.org/cgi-bin/QTLdb/index

Database of trait mapping data, i.e. QTL (phenotype / expression, eQTL), candidate gene and association data (GWAS) and copy number variations (CNV) mapped to livestock animal genomes, to facilitate locating and comparing discoveries within and between species. New data and database tools are continually developed to align various trait mapping data to map-based genome features, such as annotated genes. QTLdb is open to house QTL/association date from other animal species where feasible. Most scientific journals require that any original QTL/association data be deposited into public databases before paper may be accepted for publication. User curator accounts are provided for direct data deposit. Users can download QTLdb data from each species or individual chromosome.

Proper citation: Animal QTLdb (RRID:SCR_001748) 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.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.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   

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