Curator Dashboard

A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)

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• SciCrunch
• 13 years ago - by Anonymous

Software package for assembling, annotating, querying, and comparing transcript and expression level data that consists of two parts: * singleTCW (sTCW): Single transcript sets or assemblies; annotation; differential expression (EdgeR, DEGSeq, DESeq, GoSeq) * multiTCW (mTCW): Comparison of multiple transcript sets; ortholog grouping (e.g., OrthoMCL) It has been tested on Linux and uses Java, mySQL and optionally R.

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• SciCrunch
• 13 years ago - by Anonymous

This resource hyperlinks to systematic analysis projects, resources, laboratories, and departments at Stanford University.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

Curated public database for autism research built on information extracted from the studies on molecular genetics and biology of Autism Spectrum Disorders (ASD). The genetic information includes data from linkage and association studies, cytogenetic abnormalities, and specific mutations associated with ASD. New gene submissions are welcome. Modules: * Human Gene: thoroughly annotated list of genes that have been studied in the context of autism, with information on the genes themselves, relevant references from the literature, and the nature of the evidence. Uniquely, SFARI Gene incorporates information on both common and rare variants. * Animal Model: information about lines of genetically modified mice that represent potential models of autism. This information includes the nature of the targeting construct, the background strain and, most importantly, a thorough summary of the phenotypic features of the mice that are most relevant to autism. * Protein Interaction (PIN): compilation of all known direct protein interactions for those gene products implicated in autism. It presents both graphical and tabular views of interactomes, highlighting connections between autism candidate genes. Each protein interaction is manually verified by consultation with the primary reference. * Copy Number Variant (CNV): a parallel resource providing genetic information about all known copy number variants linked to autism. * Gene Scoring: includes a "score" for each autism candidate gene, based on an assessment of the strength of human genetic evidence.

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• SciCrunch
• 12 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented April 11, 2017. Division within the South Korean government that handled affairs of education and science. It has since been split into Ministry of Science, ICT and Future Planning and Ministry of Education.

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• SciCrunch
• 13 years ago - submitted by Andrea Stagg

Software package that provides functions for solving a family of sparse learning algorithms. The functions implemented enjoy the convergence rate of O(1/k^2), although the objective function is non-smooth. Main features: * First-Order Method. At each iteration, they only need to evaluate the function value and the gradient; and thus the algorithms can handle large-scale sparse data. * Optimal Convergence Rate. The convergence rate O(1/k^2) is optimal for smooth convex optimization via the first-order black-box methods. * Efficient Projection. The projection problem (proximal operator) can be solved efficiently. * Pathwise Solutions. The SLEP package provides functions that efficiently compute the pathwise solutions corresponding to a series of regularization parameters by the warm-start technique.

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• SciCrunch
• 12 years ago - by Anonymous

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

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• SciCrunch
• 17 years ago - by Anonymous

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).

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• SciCrunch
• 17 years ago - by Anonymous

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

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

Institute for the study of theoretical biology with a focus on evolutionary developmental biology and cultural complexity.

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• SciCrunch
• 15 years ago - submitted by Andrea Stagg

This site is about Social Anxiety Disorder, how to diagnose social anxiety, how to live and cope with social anxiety, and how to treat social anxiety. Additionally, this website also intends to educate, inform, promote self-help, and provide a way to facilitate dialog between those who suffer from social phobia.

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• SciCrunch
• 17 years ago - by Anonymous

The mission of SFARI is to improve the diagnosis, treatment, and prevention of autism and related developmental disorders. SFARI explores neuroscience from multiple directions, including molecular, cellular, systems, immunological, cognitive, behavioral, genetic, theoretical and computational perspectives. Funding for innovative scientific research is available through a peer-reviewed proposal process at regular intervals. Research projects are reviewed by a scientific advisory board and managed by the scientific director and a highly qualified staff. Proposals in multiple research areas are sought, to reflect the complex nature of autism. The Foundation supports innovative scientific projects where our involvement will play an essential role. In the course of this support, The Foundation is interested in partnering with other entities, or providing matching support where appropriate. The Simons Foundation has historically accepted only solicited grant proposals. These grant decisions are made by the Trustees of The Simons Foundation, who review applications on an ongoing basis. In the area of autism research, requests for proposals are issued on an annual basis. The Simons Foundation does not give grants to individuals, except through their institutions.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. This database provides information on the components of cellular signaling pathways and their relations to one another, which are organized into pathways called Connections Maps, which serve as the graphical interface into the database. Access to the database is free. Scientists with expertise in a given field, designated as Pathway Authorities, provide the information. With canonical or general data about cell signaling, as well as specific data about particular signaling processes in specific organisms and cells, there is information for both novices to cell signaling and experts. The Connections Maps are dynamically generated graphical interface to a database of information on the components of cellular signaling pathways and their relations to one another. Information is provided by pathway authorities with expertise in a given field. These Maps provide information on Canonical Pathways -- idealized or generalized pathways that represent common properties of a particular signaling module or pathway. Sponsors: This database is supported by AAAS.

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• SciCrunch
• 17 years ago - by Anonymous

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

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• SciCrunch
• 12 years ago - by Anonymous

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).

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 12 years ago - by Anonymous

Algorithm for identifying broad peaks in diffuse ChIP-seq datasets.

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• SciCrunch
• 13 years ago - by Anonymous