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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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https://github.com/raphael-group/THetA

An algorithm that estimates the tumor purity and clonal / subclonal copy number aberrations directly from high-throughput DNA sequencing data.

Proper citation: THetA (RRID:SCR_001860) Copy   

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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   

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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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http://www.ualberta.ca/

Public research university in Edmonton, Alberta, Canada that offers degree programs in a variety of fields including business, arts, education, engineering, nursing, and medicine.

Proper citation: University of Alberta; Alberta; Canada (RRID:SCR_001853) Copy   

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

Software that identifies cell population in flow cytometry data. It demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations. It samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting connected components estimate biological cell populations in the data sample.

Proper citation: SamSPECTRAL (RRID:SCR_001858) Copy   

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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   

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http://pga.gs.washington.edu

The SeattleSNPs PGA is focused on identifying, genotyping, and modeling the associations between single nucleotide polymorphisms (SNPs) in candidate genes and pathways that underlie inflammatory responses in humans. SeattleSNPs is focused on variation analysis in genes related to the inflammatory response. These gene targets are found in specific pathways and from interacting molecules contributing to this response. Available Resources: - Baseline assembled and complete genomic sequence and chromosomal location for candidate gene targets - Mapping of exon and repeat structure for candidate genes - Amplification primers and conditions - SNPs mapped by location in gene structure - SNPs with immediate surrounding sequence for genotype assay design - Genotypes and relative allele frequencies of the SNPs - Special features of SNPs - location (5', coding, etc.), amino acid substitutions, recurrent variation - Manuals on all protocols, data analysis procedures, and use of software tools - Workshop on genetic variation analysis and a gene submission program for variation analysis Sponsors: SeattleSNPs is funded as part of the National Heart Lung and Blood Institute's (NHLBI) Programs for Genomic Applications (PGA).

Proper citation: SeattleSNPs - Variation Discovery Resource (RRID:SCR_001859) Copy   

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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   

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http://www.sdsc.edu/

Founded in 1985, the San Diego Supercomputer Center (SDSC) enables international science and engineering discoveries through advances in computational science and data-intensive, high-performance computing. SDSC is considered a leader in data-intensive computing, providing resources, services and expertise to the national research community including industry and academia. The mission of SDSC is to extend the reach of scientific accomplishments by providing tools such as high-performance hardware technologies, integrative software technologies, and deep interdisciplinary expertise to these communities. From 1997 to 2004, SDSC extended its leadership in computational science and engineering to form the National Partnership for Advanced Computational Infrastructure (NPACI), teaming with approximately 40 university partners around the country. Today, SDSC is an Organized Research Unit of the University of California, San Diego with a staff of talented scientists, software developers, and support personnel. A broad community of scientists, engineers, students, commercial partners, museums, and other facilities work with SDSC to develop cyberinfrastructure-enabled applications to help manage their extreme data needs. Projects run the gamut from creating astrophysics visualization for the American Museum of Natural History, to supporting more than 20,000 users per day to the Protein Data Bank, to performing large-scale, award-winning simulations of the origin of the universe or how a major earthquake would affect densely populated areas such as southern California. Along with these data cyberinfrastructure tools, SDSC also offers users full-time support including code optimization, training, 24-hour help desk services, portal development and a variety of other services. As one of the NSF's first national supercomputer centers, SDSC served as the data-intensive site lead in the agency's TeraGrid program, a multiyear effort to build and deploy the world's first large-scale infrastructure for open scientific research. SDSC currently provides advanced user support and expertise for XSEDE (Extreme Science and Engineering Discovery Environment) the five-year NSF-funded program that succeeded TeraGrid in mid-2011.

Proper citation: San Diego Supercomputer Center (RRID:SCR_001856) Copy   

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http://www.dkfz.de/en/mol_embryology/axeldb.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 21, 2011. Database focusing on gene expression in the frog Xenopus laevis, it is the web companion to the research papers describing a large-scale in situ hybridization screening in Xenopus embryos. The goals of this large-scale in situ screen project are to identify genes by the characterization of their expression pattern, to partially sequence the corresponding cDNAs and to maintain a database collecting the results.

Proper citation: Axel Database (RRID:SCR_001890) Copy   

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http://hopkinsneuro.org/research/jhu_nimh/

The Johns Hopkins NIMH Center is comprised of an interdisciplinary research team who has pooled their talents to study the nature of HIV-associated neurocognitive disorders (HAND). Their aim is to translate discoveries of the pathophysiological mechanisms into novel therapeutics for HAND. Objectives * To integrate aspects of ongoing research in HAND and SIV encephalitis * Develop high-throughput and screening assays for identifying novel therapeutic compounds * Use proteomics and lipidomics approaches to indentifying surrogate markers of disease activity * Disseminate information and education about HAND through existing and new educational systems, including the JHU AIDS Education Training Center and the JHU Center for Global Clinical Education * Facilitate the entry of new investigators into Neuro-AIDS research, and to catalyze new areas of research, particularly where relevant for drug discovery or the development of validated surrogate markers

Proper citation: Johns Hopkins NIMH Research Center Novel Therapeutics of HIV-associated Cognitive Disorders (RRID:SCR_001891) Copy   

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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   

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http://lad.icmb.utexas.edu/index_smd.shtml

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. It stores raw and normalized data from microarray experiments, as well as their corresponding image files. In addition, LAD provides interfaces for data retrieval, analysis, and visualization.

Proper citation: Longhorn Array Database (RRID:SCR_001895) Copy   

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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   

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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   

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http://opencourse.org/Collaboratories/harveyproject/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. It is an international collaboration of educators, researchers, physicians, students, programmers, instructional designers and graphic artists working together to build interactive, dynamic human physiology course materials on the Web. Sponsors: This work has received funding from the US National Science Foundation.

Proper citation: Harvey Project: Open Course Collaboratories (RRID:SCR_001887) Copy   

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