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https://bcbio-nextgen.readthedocs.org/en/latest/

A python toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis.

Proper citation: bcbio-nextgen (RRID:SCR_004316) Copy   

•   Source: SciCrunch Registry

http://www.healthsystem.virginia.edu/internet/crr/ligand.cfm

This Core at the University of Virginia employs state-of-the-art methods to quantitate peptide and steroid reproductive hormones in blood and tissue. It also develops new methodology, prepares labeled reagents for immunoassays, immunocytochemistry and binding studies and assists in the transfer of technology to participating investigators. Available services: AMH ELISA, 3-ALPHA DIOL G ELISA (ON HOLD), ANDROSTENEDIONE RIA, CORTISOL HUMAN IMMULITE, CORTICOSTERONE RIA, DHEA ELISA, DHEA-SO4 HUMAN IMMULITE, DHT NON EXTRACTION RIA (ON HOLD), ESTRADIOL HUMAN & MOUSE BECKMAN COULTER RIA, ESTRADIOL RAT SIEMENS RIA, ESTRONE- RIA, FSH HUMAN IMMULITE, IGF-1 HUMAN IMMULITE, INHIBIN-A ELISA, INHIBIN-B ELISA, INSULIN HUMAN IMMULITE, LH HUMAN IMMULITE, MOUSE FSH RIA, MOUSE LH SANDWICH IRMA, PROGESTERONE RIA, PROINSULIN RIA, PROLACTIN HUMAN IMMULITE, 17a-OH-PROGESTERONE RIA, RAT FSH RIA, RAT LH SANDWICH IRMA, SHBG HUMAN IMMULITE, TESTOSTERONE RIA, SENSITIVE ESTRADIOL HUMAN & RAT RIA, SENSITIVE PROGESTERONE RIA, SENSITIVE TESTOSTERONE - RIA

Proper citation: UVA Center for Research in Reproduction Ligand Assay and Analysis Core (RRID:SCR_004318) Copy   

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http://www.ebi.ac.uk/pdbe/

The European resource for the collection, organization and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - they work to collate, maintain and provide access to the global repository of macromolecular structure data. The main objectives of the work at PDBe are: * to provide an integrated resource of high-quality macromolecular structures and related data and make it available to the biomedical community via intuitive user interfaces. * to maintain in-house expertise in all the major structure-determination techniques (X-ray, NMR and EM) in order to stay abreast of technical and methodological developments in these fields, and to work with the community on issues of mutual interest (such as data representation, harvesting, formats and standards, or validation of structural data). * to provide high-quality deposition and annotation facilities for structural data as one of the wwPDB deposition sites. Several sophisticated tools are also available for the structural analysis of macromolecules.

Proper citation: PDBe - Protein Data Bank in Europe (RRID:SCR_004312) Copy   

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http://www.caneucre.org

Cre expressing mice under the control of promoters with a design focus on the brain. Each promoter is derived from human sequence, but the resulting expression is assessed in the mouse for the activation of a LacZ reporter gene by the Cre activity. Promoters tested as large MaxiPromoters (BACs inserted into the mouse genome) and MiniPromoters (plasmid-based sequences inserted either into the mouse genome or introduced within AAV viruses). The Cre-related project continues from the Pleiades Promoter Project. Here is the list of genes for which icre/ERT2 mice are currently in development: AGTR1, CARTPT, CLDN5, CLVS2, CRH, GABRA6, HTR1A, HTR1B, KCNA4, KDM5C, MKI67, NEUROD6, NKX6-1, NOV, NPY2R, NR2E1, OLIG2, POU4F2, SLITRK6, SOX1, SOX3, SOX9,, SPRY1, VSX2

Proper citation: CanEuCre (RRID:SCR_004159) Copy   

•   Source: SciCrunch Registry

http://noble.gs.washington.edu/proj/qvality/

qvality estimates q-values and posterior error probabilities directly from score distributions. The method can be accessed via a web interface or downloaded as stand-alone software (C++ source code and binaries are available under MIT license). The qvality web server allows you to use qvality to compute posterior error probability and q-values for your data. There are two input modes: *Input the empirical score distribution and a corresponding null score distribution. The two inputs do not have to contain the same numbers of scores. *Input only the empirical p-value distribution. In this case, you must use p-values rather than raw scores. In either mode, the output is the same: a three-column file in which the first column contains sorted observed scores, the second column contains estimated q-values, and the third column contains estimated posterior error probabilities. Qvality is a C++ program for estimating two types of standard statistical confidence measures: the q-value, which is an analog of the p-value that incorporates multiple testing correction, and the posterior error probability (PEP, also known as the local false discovery rate), which corresponds to the probability that a given observation is drawn from the null distribution. In computing q-values, qvality employs a standard bootstrap procedure to estimate the prior probability of a score being from the null distribution; for PEP estimation, qvality relies upon non-parametric logistic regression. Relative to other tools for estimating statistical confidence measures, qvality is unique in its ability to estimate both types of scores directly from a null distribution, without requiring the user to calculate p-values.

Proper citation: qvality - Nonparametric estimation of posterior error probabilities (RRID:SCR_004309) Copy   

•   Source: SciCrunch Registry

http://stores.columbiabiosciences.com/

An Antibody supplier

Proper citation: Columbia Biosciences Corporation (RRID:SCR_004347) Copy   

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http://www.neuromatic.thinkrandom.com/

NeuroMatic is a collection of Igor Pro functions for analyzing electrophysiological data. By allowing users to organize their data into Sets and Groups, NeuroMatic makes it relatively easy to compute transformations and statistical analyses on their data, including scaling, alignment averaging, baseline subtraction, spike detection, stationarity analysis, rise-time computations, etc. Being open source and modular designed, NeuroMatic also allows users to develop their own analysis functions that can be easily incorporated into NeuroMatic's framework. Note, if you have reached this page in search of a freeware tool for neuronal reconstructions, you are more likely to be interested in Neuromantic, a software package that sounds like NeuroMatic, but is not quite the same. Features of NeuroMatic Include * Sorting, Scaling, Averaging, Interpolation * Max / Min / Mean / Level / Rise Time / FWHM / Slope Measurements * Stability / Stationarity Analysis * Event Detection * Waveform Template Matching * Spike Raster Plots * Interspike-Interval and Peri-Stimulus Time (PST) Histograms * Compact Easy-to-Use Interface * Modular design as a basis for your own procedures * Extra space for your own buttons and controls * Import functions for Axograph and Pclamp data * Automatic macro generation for batch processing Supporting Agencies: MRC, Wellcome Trust Spike, Event, Fit, NClamp, Acquisition, spike train, EPSP, IPSP, IPSC, EPSC

Proper citation: NeuroMatic (RRID:SCR_004186) Copy   

•   Source: SciCrunch Registry

http://www.dukecancerinstitute.org/

One of 40 centers in the country designated by the National Cancer Institute (NCI) as a comprehensive cancer center, it combines cutting-edge research with compassionate care. Its vision is to accelerate research advances related to cancer and improve Duke''s ability to translate these discoveries into the most advanced cancer care to patients by uniting hundreds of cancer physicians, researchers, educators, and staff across the medical center, medical school, and health system under a shared administrative structure.

Proper citation: Duke Cancer Institute (RRID:SCR_004338) Copy   

•   Source: SciCrunch Registry

http://www.fmi.ch/

The Friedrich Miescher Institute is devoted to fundamental biomedical research aimed at understanding the basic molecular mechanisms of health and disease. We communicate and patent our findings to enable their translation into medical application. The FMI focuses on the fields of Epigenetics, Signaling & Cancer, and Neurobiology. In these fields, the FMI has gained international recognition as a center of excellence in innovative biomedical research. Training young scientists The Friedrich Miescher Institute contributes to the training of graduate students and postdoctoral fellows. Through its PhD program, which was established as early as 1970, the FMI attracts top international students. The FMI is affiliated with the University of Basel, where most of the graduate students are enrolled and where it contributes to the teaching program. Many FMI alumni have gone on to pursue successful careers in Novartis, in other pharmaceutical companies, or in academic research. Exciting environment for academic and applied research Staff at FMI benefit from a unique scientific environment, allowing researchers, specialists and students to pursue questions that yield new scientific insights. As part of the Novartis Research Foundation, the FMI receives strong core support from the foundation. Funding is supplemented by competitive fellowships and awards from national and international funding agencies. This provides an optimal environment for both academic and applied biomedical research.

Proper citation: Friedrich Miescher Institute (RRID:SCR_004179) Copy   

•   Source: SciCrunch Registry

http://genie.weizmann.ac.il/software/nucleo_prediction.html

This tool allows you to submit a genomic sequence and to recieve a prediction of the nucleosomes positions on it, based on the nucleosome-DNA interaction model that we developed in these papers: * Segal et al., A Genomic Code for Nucleosome Positioning, Nature 2006 * Field et al., Distinct Modes of Regulation by Chromatin Encoded through Nucleosome Positioning Signals, PLoS Comp Biol. 2008 * Kaplan et al., The DNA-Encoded Nucleosome Organization of a Eukaryotic Genome, Nature 2008 We recommend using the latest version of the model (Version 3), which is applicable to all species. Paste in a sequence to analyze or upload file. You can provide multiple sequences in fasta format (separate sequences by lines starting with ''>'' followed by the sequence name). The length of each sequence must be between 147bp and 40kb bp. Note: Due to boundary effects, we highly recommend that you add at least 5000 bp of flanking sequence around your sequence of interest. You can generate the nucleosomes positioning predictions on your own machine using our executable and wrapping Perl scripts.

Proper citation: Online Nucleosomes Position Prediction by Genomic Sequence (RRID:SCR_004210) Copy   

•   Source: SciCrunch Registry

http://annotationframework.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. The DOMEO (Document Metadata Organizer) Annotation Tool, is an extensible web component enabling users to visually and efficiently create and share ontology-based stand-off annotation metadata on HTML or XML document targets - and soon images - , using the Annotation Ontology (AO) RDF model. The tool supports manual, fully automated, and semi-automated annotation with complete provenance records, as well as personal or community annotation with access authorization and control. DOMEO is just one of the components of a bigger architecture - The Annotation Framework - that uses Annotation Ontology (AO) as communication mechanism within the platform and with the external world. Acknowledgements Special thanks to Marco Ocana for his valuable contribution in bootstrapping the DOMEO project.

Proper citation: DOMEO (RRID:SCR_004170) Copy   

•   Source: SciCrunch Registry

http://genome.gsc.riken.jp/osc/english/dataresource/

A program to eliminate artifactual reads from next-generation sequencing data sets.

Proper citation: TagDust (RRID:SCR_004175) Copy   

•   Source: SciCrunch Registry

http://noble.gs.washington.edu/proj/svmvia/

Software that implements the full regularization path optimization algorithm for training a support vector machine. The support vector machine algorithm has a single hyperparameter C that regularizes the learned model. Recently, Hastie et al. (2004) described an algorithm for finding the SVM solution for all possible values of this regularization parameter. An efficient C++ implementation of this algorithm is presented. For large values of C, it is often faster to find the entire regularization path than to train a single model.

Proper citation: svmvia (RRID:SCR_004209) Copy   

•   Source: SciCrunch Registry

http://figshare.com/

Repository for all data, figures, theses, publications, posters, presentations, filesets, videos, datasets, negative data in a citable, shareable and discoverable manner with Digital Object Identifiers. Allows to upload any file format to be made visualisable in the browser so that figures, datasets, media, papers, posters, presentations and filesets can be disseminated in a way that the current scholarly publishing model does not allow. Features integration with ORCID, Symplectic Elements, can import items from Github and is a source tracked by Altmetric.com. Figshare gives users unlimited public space and 1GB of private storage space for free. Data are digitally preserved by CLOCKSS. Supported by Digital Science, a division of Macmillan Publishers Limited, as a community-based, open science project that retains its autonomy.

Proper citation: FigShare (RRID:SCR_004328) Copy   

•   Source: SciCrunch Registry

http://www.grissom.gr/stranger/

StRAnGER (Statistical Ranking of ANotated Genomic Experimental Results) is a web application for the automated statistical analysis of annotated gene profiling experiments, exploiting controlled biological vocabularies, like the Gene Ontology or the KEGG pathways terms. Starting from annotated lists of differentially expressed genes StRAnGER repartitions and reorders the initial distribution of terms to define a new distribution of elements where each element pools terms holding the same enrichment score. The elements are then prioritized according to StRAnGER''''s algorithm and, by applying bootstrapping techniques, a corrected measure of the statistical significance of these elements is derived, enabling the selection of terms mapped to these elements, unambiguously associated with respective significant gene sets. Besides their high statistical score, another selection criterion for the terms is the number of their members, something that incurs a biological prioritization in line with a Systems Biology context. Platform: Online tool

Proper citation: StRAnGER (RRID:SCR_004247) Copy   

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http://www.psidev.info/MOD

The Proteomics Standards Initiative (PSI) aims to define community standards for data representation in proteomics to facilitate data comparison, exchange and verification. The protein modification workgroup focuses on developing a consensus nomenclature and provide an ontology reconciling in a hierarchical representation the complementary descriptions of residue modifications. The protein modification ontology (PSI-MOD) is available in OBO format or in OBO.xml. A spreadsheet containing the mapping of the descriptive labels used in various databases and search engines, the consensus list of proposed short name for protein modifications established by collaborative effort of mass spectrometry community, and the proposed rules and recommendations for this nomenclature are available. These short names are included in the ontology as synonyms of the corresponding terms.

Proper citation: PSI-MOD (RRID:SCR_004198) Copy   

•   Source: SciCrunch Registry

https://www.hgsc.bcm.edu/software/mercury

An automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. The analysis pipeline is deployed in local hardware and the Amazon Web Services cloud via the DNAnexus platform.

Proper citation: Mercury (RRID:SCR_004231) Copy   

•   Source: SciCrunch Registry

http://ratmine.mcw.edu/ratmine/begin.do

RatMine integrates data from RGD, UniProtKB, NCBI, KEGG and other sources to form a web-based data warehouse and tool set tailored for rat based data research. Search RatMine by entering names, identifiers, or keywords for genes, proteins, pathways, papers, etc. Additionally, we support programmatic access to our data through Application Programming Interface - choose from Perl or Java API. RatMine is a data warehouse that integrates many diverse biological data sets. The main focus is R. norvegicus genomics and proteomics. By integrating such data into one place it is possible to construct queries across domains of biological knowledge. The RatMine user interface is designed to go beyond simply looking up an identifier and viewing a report page. Some of the features include: * Quick Search is available just like on other sites, type in an identifier to see a report page. * Template queries are ''canned'' queries that provide a simple form to perform a specific task. You can create your own templates if you log in. * Lists lets you operate on whole lists of data at once. You can upload lists or save them from results tables. We also create useful public lists for everyone to use. * MyMine lets you create an account to save your own queries, bags and templates, as well as marking public templates as favorites.

Proper citation: RatMine (RRID:SCR_004190) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/artemis/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Free genome browser and annotation tool that allows visualization of sequence features, next generation data and the results of analyses within the context of the sequence, and also its six-frame translation. Artemis is free software and is distributed under the terms of the GNU General Public License. Artemis is written in Java, and is available for UNIX, Macintosh and Windows systems. It can read EMBL and GENBANK database entries or sequence in FASTA, indexed FASTA or raw format. Other sequence features can be in EMBL, GENBANK or GFF format.

Proper citation: Artemis: Genome Browser and Annotation Tool (RRID:SCR_004267) Copy   

•   Source: SciCrunch Registry

http://www.alz.co.uk/

Alzheimer''s Disease International (ADI) believes that the key to winning the fight against dementia lies in a unique combination of Global Solutions and local knowledge. As such, it works locally, by empowering Alzheimer associations to promote and offer care and support for people with dementia and their carers, while working globally to focus attention on dementia. Our board is composed of people from around the world, and our staff team is based in London. ADI is the international federation of Alzheimer associations around the world, in official relations with the World Health Organization. Each member is the Alzheimer association in their country who support people with dementia and their families. ADI''s vision is an improved quality of life for people with dementia and their families throughout the world. ADI runs the Alzheimer University, a series of practical workshops aimed at helping the staff and volunteers of Alzheimer associations build and strengthen their organisations. ADI holds an annual international conference which is the longest running international conference on dementia. The conference is a unique multi-disciplinary event which unites people with an interest in dementia from around the world. World Alzheimer''s Day, celebrated on September 21 each year, is an opportunity to raise global awareness about dementia and its impact on families and the important work of our members throughout the world. Medical research is also important, and some of ADI''s member Alzheimer associations actively support research in their own countries. More information about research can be found on the web sites of Alzheimer''s Association (USA), Alzheimer''s Society (UK), Alzheimer Society of Canada, or the association in your country. For the fourth year, the Fondation M��d��ric Alzheimer and ADI are running Alzheimer''s Awards for evidence-based psychosocial interventions for people with dementia and their carers.

Proper citation: Alzheimers Disease International (RRID:SCR_004303) Copy   

•   Source: SciCrunch Registry