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http://salilab.org/modeller/modeller.html

Software tool as Program for Comparative Protein Structure Modelling by Satisfaction of Spatial Restraints. Used for homology or comparative modeling of protein three dimensional structures. User provides alignment of sequence to be modeled with known related structures and MODELLER automatically calculates model containing all non hydrogen atoms.

Proper citation: MODELLER (RRID:SCR_008395) Copy   

•   Source: SciCrunch Registry

http://biolit.ucsd.edu/doc/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 16, 2016. The establishment of open access literature makes it possible for knowledge to be extracted from scholarly articles and included in other resources. BioLit aims to extract database identifiers and rich meta-data from open access articles in the life sciences and integrate that information with existing biological databases. We have begun prototyping this effort using a clone of the RCSB Protein Data Bank, a database of macromolecular structures. Cyberinfrastructure is integral to all aspects of conducting experimental research and distributing those results. However, it has yet to make a similar impact on the way we communicate that information. Peer-reviewed publications have long been the currency of scientific research as they are the fundamental unit through which scientists communicate with and evaluate each other. However, in striking contrast to the data, publications have yet to benefit from the opportunities offered by cyberinfrastructure. While the means of distributing publications has vastly improved, publishers have done little else to capitalize on the electronic medium. In particular, semantic information describing the content of these publications is sorely lacking, as is the integration of this information with data in public repositories. This is confounding considering that many basic tools for marking-up and integrating publication content in this manner already exist, such as a centralized literature database, relevant ontologies, and machine-readable document standards. We believe that the research community is ripe for a revolution in scientific communication and that the current generation of scientists will be the one to push it forward. These scientists, generally graduate students and new post-docs and have grown up with cyberinfrastructure as a part of their daily lives, not just a specialized aspect of their profession. They have a natural ability to do science in an electronic environment without the need for printed publications or static documents and, in fact, can feel quite limited by the traditional format of a publication. Perhaps most importantly, they appreciate that the sheer amount of data and the number of publications is prohibitive to the traditional methods of keeping current with the literature. Fink, L., Bourne, P. Reinventing Scholarly Communication for the Electronic Age, CTWatch Quarterly, Volume 3, Number 3, August 2007., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BioLit (RRID:SCR_008270) Copy   

•   Source: SciCrunch Registry

http://www.fa-petition.org/en/attivita/progetti2008.html

The aim of this resource is to facilitate and promote, even through fund-raising, the scientific research for the treatment of Friederich''s Ataxia. The mission of this portal is to: - To distribute information to the people affected by the disease and to make the general population aware. - Promote, fund and support the diagnosis, research, cure and potential treatments. - Promote the cooperation with other voluntary associations both national and international. Sponsors: This resource is supported by the RUDI Committee. Keywords: Research, Diagnosis, Cure, Treatment, Disease, Scientific, Friederich''s Ataxia,

Proper citation: ATASSIA DI FRIEDREICH - PROGETTI 2006 (RRID:SCR_008391) Copy   

•   Source: SciCrunch Registry

http://cprc.rcm.upr.edu/

Center for the study of non-human primates. Its mission is the study and use of non-human primates as models for studies of social and biological interactions and for the discovery of methods of prevention, diagnosis and treatment of diseases that afflict humans. Through the stewardship of three unique facilities—Cayo Santiago Field Station, Sabana Seca Field Station, and the Laboratory of Primate Morphology supports a diverse range of research programs that enhance understanding of primate biology and behavior, with direct applications in biomedical and translational research.

Proper citation: Caribbean Primate Research Center (RRID:SCR_008345) Copy   

•   Source: SciCrunch Registry

http://griffin.cbrc.jp/

Griffin (G-protein-receptor interacting feature finding instrument) is a high-throughput system to predict GPCR - G-protein coupling selectively with the input of GPCR sequence and ligand molecular weight. This system consists of two parts: 1) HMM section using family specific multiple alignment of GPCRs, 2) SVM section using physico-chemical feature vectors in GPCR sequence. G-protein coupled receptors (GPCR), which is composed of seven transmembrane helices, play a role as interface of signal transduction. The external stimulation for GPCR, induce the coupling with G-protein (Gi/o, Gq/11, Gs, G12/13) followed by different kinds of signal transduction to inner cell. About half of distributed drugs are intending to control this GPCR - G-protein binding system, and therefore this system is important research target for the development of effective drug. For this purpose, it is necessary to monitor, effectively and comprehensively, of the activation of G-protein by identifying ligand combined with GPCR. Since, at present, it is difficult to construct such biochemical experiment system, if the answers for experimental results can be prepared beforehand by using bioinformatics techniques, large progress is brought to G-protein related drug design. Previous works for predicting GPCR-G protein coupling selectivity are using sequence pattern search, statistical models, and HMM representations showed high sensitivity of predictions. However, there are still no works that can predict with both high sensitivity and specificity. In this work we extracted comprehensively the physico-chemical parameters of each part of ligand, GPCR and G-protein, and choose the parameters which have strong correlation with the coupling selectivity of G-protein. These parameters were put as a feature vector, used for GPCR classification based on SVM.

Proper citation: G protein receptor interaction feature finding instrument (RRID:SCR_008343) Copy   

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http://www.xiphophorus.txstate.edu/

Supplier of xiphophorus (platyfish or swordtails) from pedigreed parental lines, representing variety of species. In addition to supplying strains and providing consultation on husbandry and genetic questions, the XGSC produces custom interspecies hybrids (both first generation F1, and backcross hybrid generation BC1) for a variety of projects.

Proper citation: Xiphophorus Genetic Stock Center (RRID:SCR_008340) Copy   

•   Source: SciCrunch Registry

http://www.med.nus.edu.sg/ant/histonet/txt/menu/nervmenu.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 18, 2013. 15 annotated electron micrographs of different parts of the nervous system. Different nerve tissues are depicted.

Proper citation: Nerve Tissue (RRID:SCR_008219) Copy   

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http://www.nature.com/nature/supplements/collections/

This website provides summary collections written for a broad audience highlighting some of the significant advances in a particular field. These are not scientific articles although they may reference scientific work. Sponsors: This resource is supported by Nature.com

Proper citation: Nature Supplements: Collections archive (RRID:SCR_008337) Copy   

•   Source: SciCrunch Registry

http://www.snprc.org/

Center that supports studies of nonhuman primate models of human diseases, including common chronic diseases and infectious diseases and the effects that genetics and the environment have on physiological processes and disease susceptibility. SNPRC encourages the use of its resources by investigators from the national and international biomedical research communities.

Proper citation: Southwest National Primate Research Center (RRID:SCR_008292) Copy   

•   Source: SciCrunch Registry

http://www.uhnres.utoronto.ca/facilities/wcif/download.php

The ImageJ installations below correspond to the WCIF ImageJ manual. The manual is written for this particular installation of ImageJ. This ImageJ installation has, among other plugins, one that links to an online version of the manual. The online manual is more up-to-date than the PDF version. Windows users Download WCIF ImageJ bundle (~23Mb) v1.34i, 3rd March 2005 with J2SE 5.0 (formerly J2SE 1.5). For Windows: download and run program. Mac and Linux users Download your OS specific version of ImageJ from the ImageJ website then extract the following file to the plugins folder. Download WCIF ImageJ bundle plugins only (~2Mb) This contains only the plugins, IJ preferences, LUTs and plugin source code. Image Processing and Analysis Software ImageJ LSM Browser (*.lsm) Axiovision viewer (*.zvi) Manufacturers of our microscopes and related equipment Zeiss - Microscopes and imaging systems. P.A.L.M. Microlaser Technologies - Manufacturer of our laser capture system. Sutter Instruments - Micromanipulators. Uniblitz - Shutters. Ludl - Manufacturers of our motorised x-, y-stage Hamamatsu - Digital cameras. Molecular Probes - Dyes and reagents. Scanalytics - Image acquisition and processing software. MicroBrightField - Developers of the Neurolucida and Stereo Investigator software. DVC - Digital cameras. Bitplane - Developers of the Imaris suite of software. AutoQuant - Developers of the AutoDeblur deconvolution software

Proper citation: Wright Cell Imaging Facility (RRID:SCR_008488) Copy   

•   Source: SciCrunch Registry

http://www.dialog.com

Dialog provides critical information from the world''s most authoritative publishers, combined with the tools to search every bit of it with speed and precision. With direct operations in 27 countries, Dialog products and services are a combination of highly accurate online research tools offering access to unique and relevant databases designed to meet the specific needs of a wide range of users. Information professionals and end-users at business, professional, scientific, academic and government organizations in more than 100 countries prize Dialog services to meet their searching needs. As part of the Deep Web, which is estimated to be 500 times larger than the content accessible via Web search engines, Dialog products offer unparalleled depth and breadth of content coupled with the ability to search with precision and speed. Our collection of over 900 databases handles more than 700,000 searches and delivers over 17 million document page views per month. Searchable content on Dialog services includes articles and reports from thousands of real-time news feeds, newspapers, broadcast transcripts and trade publications, plus market research reports and analyst notes providing support for financial decision-making, as well as in-depth repositories of scientific and technical data, patents, trademarks and other intellectual property data. Additional content areas include government regulations, social sciences, food and agriculture, reference, energy and environment, chemicals, pharmaceuticals and medicine.

Proper citation: Dialog (RRID:SCR_008482) Copy   

•   Source: SciCrunch Registry

http://tree.bio.ed.ac.uk/software/figtree

A graphical viewer of phylogenetic trees and a program for producing publication-ready figures. It is designed to display summarized and annotated trees produced by BEAST.

Proper citation: FigTree (RRID:SCR_008515) Copy   

•   Source: SciCrunch Registry

http://www.ebtox.org

This website is an invitation. an invitation to join scientists and stakeholders in an effort to review the scientific basis of traditional toxicological risk assessment, to provide the toxicological community with the tools it needs to efficiently and transparently judge risks of a diversifying nature and to make toxicology thus fit to meet the challenges of the 21st century. an invitation to participate in the inception and continuous implementation of a new movement in toxicology that aims at adopting an evidence-based approach. an invitation to help bridging the gap between modern toxicological science and risk assessment in order to exploit the wealth of information from new technologies in modern life sciences & toxicological research and to arrive at informed, transparent, judicious and conscientious decisions made on the basis of all evidence available. an invitation to develop a framework that allows combining precious expert insight grown over years of practical experience with structured approaches in basic science, in method assessment and in decision-making. Such evidence-based toxicology might help to make the best possible use of all sources of evidence in an efficient, productive, reliable, acceptable and transparent manner. Why do we need evidence-based toxicology (EBT)? Toxicology and the delivery of effective safety assessment critically relies on concepts and understanding generated by basic scientific research and must therefore adapt constantly to advances in knowledge. However, particularly from the perspective of regulatory toxicology, some of the assessment paradigms and methodologies were established decades ago and have changed little in response to scientific progress. At the same time, changes in our understanding of human disease, changes in the types of product now requiring safety assessment, and changes in the legislative landscape and public expectations pose significant challenges for industry, academia and regulators alike. It is necessary to challenge the status quo and ensure that as a matter of course best scientific practice and technical sophistication is reflected in safety assessment practices such that current and future challenges can be met. It is important therefore to ensure that structures are available that will encourage, facilitate and support a process of critical appraisal and renewal of the toxicological repertoire available for safety assessment. Part of this process is to embrace evidence-based toxicology such that the best possible scientific evidence is applied to judge product safety and likely risks to human health.

Proper citation: Evidence Based Toxicology (RRID:SCR_008507) Copy   

•   Source: SciCrunch Registry

http://www.biodas.org

The Distributed Annotation System (DAS) defines a communication protocol used to exchange annotations on genomic or protein sequences. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. The advantages of this system are that control over the data is retained by data providers, data is freed from the constraints of specific organisations and the normal issues of release cycles, API updates and data duplication are avoided. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities. A DAS-enabled website or application can aggregate complex and high-volume data from external providers in an efficient manner. For the biologist, this means the ability to plug in the latest data, possibly including a user''s own data. For the application developer, this means protection from data format changes and the ability to add new data with minimal development cost. Here are some examples of DAS-enabled applications or websites for end users: :- Dalliance Experimental Web/Javascript based Genome Viewer :- IGV Integrative Genome Viewer java based browser for many genomes :- Ensembl uses DAS to pull in genomic, gene and protein annotations. It also provides data via DAS. :- Gbrowse is a generic genome browser, and is both a consumer and provider of DAS. :- IGB is a desktop application for viewing genomic data. :- SPICE is an application for projecting protein annotations onto 3D structures. :- Dasty2 is a web-based viewer for protein annotations :- Jalview is a multiple alignment editor. :- PeppeR is a graphical viewer for 3D electron microscopy data. :- DASMI is an integration portal for protein interaction data. :- DASher is a Java-based viewer for protein annotations. :- EpiC presents structure-function summaries for antibody design. :- STRAP is a STRucture-based sequence Alignment Program. Hundreds of DAS servers are currently running worldwide, including those provided by the European Bioinformatics Institute, Ensembl, the Sanger Institute, UCSC, WormBase, FlyBase, TIGR, and UniProt. For a listing of all available DAS sources please visit the DasRegistry. Sponsors: The initial ideas for DAS were developed in conversations with LaDeana Hillier of the Washington University Genome Sequencing Center.

Proper citation: Distributed Annotation System (RRID:SCR_008427) Copy   

•   Source: SciCrunch Registry

http://biosig.sourceforge.net/

Software library for processing of electroencephalogram (EEG) and other biomedical signals like electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), respiration, and so on. Biosig contains tools for quality control, artifact processing, time series analysis, feature extraction, classification and machine learning, and tools for statistical analysis. Many tools are able to handle data with missing values (statistics, time series analysis, machine learning). Another feature is that more then 40 different data formats are supported, and a number of converters for EEG,, ECG and polysomnography are provided. Biosig has been widely used for scientific research on EEG-based BraiN-Computer Interfaces (BCI), sleep research, and ECG and HRV analysis. It provides software interfaces several programming languages (C, C++, Matlab/Octave, Python), and it provides also an interactive viewing and scoring software for adding, and editing of annotations, markers and events.

Proper citation: BioSig: An Imaging Bioinformatics System for Phenotypic Analysis (RRID:SCR_008428) Copy   

•   Source: SciCrunch Registry

http://biq-analyzer.bioinf.mpi-sb.mpg.de

BiQ Analyzer is a software tool for easy visualization and quality control of DNA methylation data from bisulfite sequencing. Highlights: - End-to-end support of the analysis process: from raw sequence files to a comprehensive documentation and visualization. - Automatically generate publication-quality lollipop diagrams (show example.) - Integrated 1-click multiple sequence alignment. - Automated CpG highlighting- never spend your time highlighting CpGs by hand anymore. - Open electropherogram files to check for sequencing problems (requires an electropherogram viewer such as Chromas LITE.) - Generate MethDB-compatible DNA methylation files for database submission. - Factor 5 speedup of sequence analysis while at the same time achieving better data quality. Intended users: - Anyone who works with DNA methylation data from bisulfite sequencing. - Occasional users as well as experts (the former will benefit from the help that the program gives in order to achieve a good quality management whereas the latter will save hours and days of tedious work.) Sponsors: This resource is supported by the Max Planck Institute. Keywords: Software, Visualization, DNA, Methylation, Data, Bisulfite, Sequencing, Electropherogram, Analysis,

Proper citation: BiQ Analyzer: A Software Tool for DNA Methylation Analysis (RRID:SCR_008423) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/PostGenomics/S_pombe/

The laboratory studies global gene expression programs in fission yeast (S. pombe). They apply a wide range of integrated approaches to analyse regulatory networks during cell proliferation, differentiation and quiescence including genetic and environmental perturbations. They are also interested in genetic diversity, genome evolution, and the complex interactions between genotypes, phenotypes, and the environment. The relative simplicity of the yeast cell promises a deeply satisfying, systems-level understanding of its inner workings within our life time Sponsors: This research is mainly funded by Cancer Research UK and the EC FP7 PhenOxiGEn project. Keywords: Gene, Expression, S.pombe, Yeast, Cell, Proliferation, Differentiation, Environmental, Genetic, Diversity, Genome, Evolution, Genotype, Phenotype, Environment,

Proper citation: Bahler Laboratory: Genome Regulation (RRID:SCR_008422) Copy   

•   Source: SciCrunch Registry

http://qneuro.rutgers.edu

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The brain is made of billions of neurons, which together form the world''s most powerful information-processing machine. Despite decades of research, the fundamental principle by which these cells work together is still unknown. Many theories for brain function have been proposed over the last century. But only in the last few years has it become possible to record simultaneously from large enough numbers of neurons to put these theories to the test experimentally. This is an unprecedented opportunity, but it opens up a new question: how do we go from the gigabytes of experimental data that we now have, to concise conclusions about the function of the brain? The data processing methods traditionally used in neuroscience are not sophisticated enough to exploit this new flood of information. Fortunately, modern statistics and machine learning theory is making great strides in precisely the type of techniques needed to process these large multivariate databases. By applying these methods to neuronal data, we can now test long-standing hypotheses about brain function. The Cell Assembly The main focus of our research is an experimental search for cell assemblies. Before describing what a cell assembly is, it will be useful to describe what it is not. The brain is often thought of as a feed-forward system. In this scheme, sensory information is processed by successive levels of cortical analyzers, each of which transforms the results of previous levels, until sensory information is in a suitable form to guide the animals behavior. In support of this idea, the pattern of connections in the cortex does appear to respect a hierarchical organization, with the output of low-level areas corresponding to a single sensory modality being integrated into high-level multi-modal areas. Responses in higher-level sensory areas appear to have more complex responses to sensory stimuli, in agreement with increased abstraction as the hierarchy is traversed. However, there are several levels at which this feed-forward picture is incomplete. At the circuit diagram level, there more connections projecting across and down the hierarchy, than there are feed-forward projections. What''s more, if information were processed in a strictly feed-forward manner, one would expect a neuron to respond identically to repeated presentations of the same sensory stimulus. Although this is a fairly good approximation in primary sensory areas of cortex, in high-level structures responses are often more variable than expected from strict sensory control. Finally, although feed-forward processing can describe how an animal could perform simple stimulus-response behaviors, it cannot explain more complex top-down behaviors such as memory or thought. An alternative point of view, put forward over 50 years ago by Canadian psychologist Donald Hebb, holds that recurrent and feedback connections play an essential role in brain function. The principal actor in this view is the cell assembly, an anatomically distributed subset of neurons, amongst which mutually excitatory connections have been strengthened by repeated co-activation, allowing the assembly to later maintain its activity through reverberation without direct sensory stimulation. This theory allows for sensory-response behavior, and also behavior resulting purely from internally generated cognitive activity, by the sequential activation of a series of assemblies, leading in turn to the production of motion. In our research, we search for signatures of assembly activity in simultaneous recordings from multiple neurons, and aim to characterize the properties of assembly activity in ways not possible from theory alone. Software for Automatic Clustering KlustaKwik is a program developed in the lab for automatic cluster analysis, specifically designed to run fast on large data sets. In order facilitate open-source development, it is now located at klustakwik.sourceforge.net. This study was supported by NIH grants MH073245 and DC009947; NSF grant SBE-0542013 to the Temporal Dynamics of Learning Center, an NSF Science of Learning Center; a National Institute on Deafness and Other Communication Disorders, NIH, grant DC-005787-01A1; and a Spanish grant FIS 2006-09294. K.D.H. is an Alfred P. Sloan fellow. We would like to dedicate this work to the memory of D. J. Amit.

Proper citation: Rutgers University Quantitative Neuroscience Laboratory (RRID:SCR_008541) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/cgi-bin/annotation/disease_vector/aedes_aegypti/blast_page.cgi, http://www.broadinstitute.org/cgi-bin/annotation/disease_vector/aedes_aegypti/blast_page.cgi

The goals of this sequencing effort are to produce and publicly release a whole-genome assembly and auto-annotation of the Aedes genome representing 8X sequence coverage. In collaboration, these centers have delivered the target 8X draft coverage of the disease vector genome. Assembly of the genome was performed using the Broad''s whole genome assembly package ARACHNE (Batzoglou et al., 2002 and Jaffe et al., 2003). The Aedes genome will be annotated in a collaborative effort involving both MSCs and Vectorbase, which is a bioinformatics resource center at the University of Notre Dame. Sponsor: This resource is supported by the National Institute of Allergy and Infectious Diseases. Keywords: Genome, BLAST, Similarity, Search, Engine, Sequence, Bioinformatics, Resource,

Proper citation: BLAST Similarity Search (RRID:SCR_008419) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/mpg/grail/

A tool to examine relationships between genes in different disease associated loci. Given several genomic regions or SNPs associated with a particular phenotype or disease, GRAIL looks for similarities in the published scientific text among the associated genes. As input, users can upload either (1) SNPs that have emerged from a genome-wide association study or (2) genomic regions that have emerged from a linkage scan or are associated common or rare copy number variants. SNPs should be listed according to their rs#''s and must be listed in HapMap. Genomic Regions are specified by a user-defined identifier, the chromosome that it is located on, and the start and end base-pair positions for the region. Grail can take two sets of inputs - Query regions and Seed regions. Seed regions are definitely associated SNPs or genomic regions, and Query regions are those regions that the user is attempting to evaluate agains them. In many applications the two sets are identical. Based on textual relationships between genes, GRAIL assigns a p-value to each region suggesting its degree of functional connectivity, and picks the best candidate gene. GRAIL is developed by Soumya Raychaudhuri in the labs of David Altshuler and Mark Daly at the Center for Human Genetic Research of Massachusetts General Hospital and Harvard Medical School, and the Broad Institute. GRAIL is described in manuscript, currently in preparation.

Proper citation: Gene Relationships Across Implicated Loci (RRID:SCR_008537) Copy   

•   Source: SciCrunch Registry