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A Web-based Tool for High-throughput Primer and Probe Design. The program has its different utilities available on its web server. A standalone version is also available. Algorithms: * SSPD - Sequence Specific Primer Design: to design primers for each of the specific sequences given by the user in the query input file against any alternate potential hybridization with any of the sequences given in the database input file. * PSPD - Probe Specific Primer Design: to design primers it selects the gene-specific fragments (probes) to design primer pairs for their PCR amplification. * FSPD Fragment Specific Primer Design: primer design algorithm used when there is a very long query sequence for which multiple primers are required for its amplification. * Check Binding Specificity * Probe Design Only: Probe design algorithm could be used to find sequence-specific probes, which doesn''t show any blast hit against database. Such probe design has been used for targeted sequencing like agilent sure-select technology with next-generation sequencing.
Proper citation: PRIMEGENS (RRID:SCR_005474) Copy
http://science.education.nih.gov/home2.nsf/feature/index.htm
The NIH Office of Science Education (OSE) coordinates science education activities at the NIH and develops and sponsors science education projects in house. These programs serve elementary, secondary, and college students and teachers and the public. Activities * Develop curriculum supplements and other educational materials related to medicine and research through collaborations with scientific experts at NIH * Maintain a website as a central source of information about NIH science education resources * Establish national model programs in public science education, such as the NIH Mini-Med School and Science in the Cinema * Promote science education reform as outlined in the National Science Education Standards and related guidelines The OSE was established in 1991 within the Office of Science Policy of the Office of the Director of the National Institutes of Health. The NIH is the world''s foremost biomedical research center and the U.S. federal government''s focal point for such research. It is one of the components of the Department of Health and Human Services (HHS). The Office of Science Education (OSE) plans, develops, and coordinates a comprehensive science education program to strengthen and enhance efforts of the NIH to attract young people to biomedical and behavioral science careers and to improve science literacy in both adults and children. The function of the Office is as follows: (1) develops, supports, and directs new program initiatives at all levels with special emphasis on targeting students in grades kindergarten to 16, their educators and parents, and the general public; (2) advises NIH leadership on science education issues; (3) examines and evaluates research and emerging trends in science education and literacy for policy making; (4) works closely with the NIH extramural, intramural, women''s health, laboratory animal research, and minority program offices on science education special issues and programs to ensure coordination of NIH efforts; (5) works with NIH institutes, centers, and divisions to enhance communication of science education activities; and (6) works cooperatively with other public- and private-sector organizations to develop and coordinate activities.
Proper citation: NIH Office of Science Education (RRID:SCR_005603) Copy
http://www.esourceresearch.org/
Inside e-Source you will find 20 interactive chapters with authoritative answers to methodological questions on behavioral and social science research. With contributions from a team of international experts, this anthology provides the latest information on addressing emerging challenges in public health. Book contents include: Setting the Scene, Describing How, Explaining Why, What Works, Emerging Issues. Tables, Figures, Exercises and Examples are included. Login for enhanced functionality. Contents: * Appropriate Research Methods * ''Science'' in the Social Sciences * Design Decisions in Research * Theory Development * Social and Behavioral Theories * Sample Surveys * Social Survey Data Collection * Administrative Data Systems * Observational Studies * Qualitative Methods * Conversation Analysis * Software and Qualitative Analysis * Clinical Trials * Cluster Unit Randomized Trials * Ethical Challenges * Multilevel Modeling * Objective Measurement of Subjective Phenomena * Measuring Socioeconomic Status * Evaluating the Quality of Health Care * Patient-Reported Outcomes
Proper citation: e-Source: Behavioral and Social Sciences Research (RRID:SCR_005627) Copy
http://grants.nih.gov/podcasts/All_About_Grants/index.htm
The Office of Extramural Research (OER) presents conversations with NIH staff members. Designed for investigators, fellows, students, research administrators, and others, we provide insights on grant topics from those who live and breathe the information. In mp3 and updated monthly. Transcripts are also available. So You Wanna... Keep Up with What''''s Hot? Prepare a Successful Grant Application? Suggest a Topic? Understand How Your Grant is Reviewed? Be an NIH Investigator?
Proper citation: All About Grants Podcast (RRID:SCR_005621) Copy
A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.
Proper citation: 3D Slicer (RRID:SCR_005619) Copy
http://great.stanford.edu/public/html/splash.php
Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool
Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).
Proper citation: UM-BBD (RRID:SCR_005787) Copy
Ratings or validation data are available for this resource
Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.
Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy
http://www.patternlabforproteomics.org/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible
Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy
http://www.essentialtremor.us/
Finding a cure for any neurological disorder begins with the scientific study of the disorder''s causes, processes, and development in the brain. For essential tremor (ET), rigorous study of this kind had not been undertaken until 2003, when the Essential Tremor Centralized Brain Repository (ETCBR) was established at Columbia University. For the past five years, brain tissue from ET donors has been collected, processed and compared alongside age-matched control brains at the ETCBR, and already several significant findings have been made. However, there is still much to learn and a severe shortage of ET brains for scientific study. If you have been diagnosed with essential tremor, donating your brain tissue in the hours immediately after your death is of utmost importance in providing crucial information about what causes ET. Direct analysis of the shape and number of nerve cells and their content will provide medical researchers with the information they need in order to understand this complex illness. By advancing our medical knowledge of ET, the gift of brain tissue is a central piece of the puzzle in the search to develop better treatments and find a cure.
Proper citation: Essential Tremor Centralized Brain Repository (RRID:SCR_004464) Copy
The National Alliance for Medical Image Computing (NA-MIC) is a multi-institutional, interdisciplinary team of computer scientists, software engineers, and medical investigators who develop computational tools for the analysis and visualization of medical image data. The purpose of the Center is to provide the infrastructure and environment for the development of computational algorithms and open-source technologies, and then oversee the training and dissemination of these tools to the medical research community. Electronic resources provided by NA-MIC include software, data, tutorials, presentations, and more.
Proper citation: National Alliance for Medical Image Computing (RRID:SCR_004460) Copy
http://www.ncbi.nlm.nih.gov/biosystems/
Database that provides access to biological systems and their component genes, proteins, and small molecules, as well as literature describing those biosystems and other related data throughout Entrez. A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. BioSystem records list and categorize components, such as the genes, proteins, and small molecules involved in a biological system. The companion FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems. A number of databases provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. This database was developed as a complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data. The NCBI BioSystems Database currently contains records from several source databases: KEGG, BioCyc (including its Tier 1 EcoCyc and MetaCyc databases, and its Tier 2 databases), Reactome, the National Cancer Institute's Pathway Interaction Database, WikiPathways, and Gene Ontology (GO). It includes several types of records such as pathways, structural complexes, and functional sets, and is desiged to accomodate other record types, such as diseases, as data become available. Through these collaborations, the BioSystems database facilitates access to, and provides the ability to compute on, a wide range of biosystems data. If you are interested in depositing data into the BioSystems database, please contact them.
Proper citation: NCBI BioSystems Database (RRID:SCR_004690) Copy
Non-profit academic organization for research and services in bioinformatics. Provides freely available data from life science experiments, performs basic research in computational biology, and offers user training programme, manages databases of biological data including nucleic acid, protein sequences, and macromolecular structures. Part of EMBL.
Proper citation: European Bioinformatics Institute (RRID:SCR_004727) Copy
Common repository for diverse human microbiome datsets and minimum reporting standards for Common Fund Human Microbiome Project.
Proper citation: HMP Data Analysis and Coordination Center (RRID:SCR_004919) Copy
http://www.proconsortium.org/pro/
An ontological representation of protein-related entities by explicitly defining them and showing the relationships between them. Each PRO term represents a distinct class of entities (including specific modified forms, orthologous isoforms, and protein complexes) ranging from the taxon-neutral to the taxon-specific. The ontology has a meta-structure encompassing three areas: proteins based on evolutionary relatedness (ProEvo); protein forms produced from a given gene locus (ProForm); and protein-containing complexes (ProComp). NOTICE: The PRO ID format has changed from PRO: to PR: (e.g. PRO:000000563 is now PR:000000563).
Proper citation: PR (RRID:SCR_004964) Copy
https://sites.google.com/site/jingyijli/SLIDE.zip
Software package that takes exon boundaries and RNA-Seq data as input to discern the set of mRNA isoforms that are most likely to present in an RNA-Seq sample. It is based on a linear model with a design matrix that models the sampling probability of RNA-Seq reads from different mRNA isoforms. To tackle the model unidentifiability issue, SLIDE uses a modified Lasso procedure for parameter estimation. Compared with deterministic isoform assembly algorithms (e.g., Cufflinks), SLIDE considers the stochastic aspects of RNA-Seq reads in exons from different isoforms and thus has increased power in detecting more novel isoforms. Another advantage of SLIDE is its flexibility of incorporating other transcriptomic data such as RACE, CAGE, and EST into its model to further increase isoform discovery accuracy. SLIDE can also work downstream of other RNA-Seq assembly algorithms to integrate newly discovered genes and exons. Besides isoform discovery, SLIDE sequentially uses the same linear model to estimate the abundance of discovered isoforms.
Proper citation: SLIDE (RRID:SCR_005137) Copy
NIH established expectations for sharing data obtained through NIH-funded genome-wide association studies (GWAS) with the implementation of the GWAS Policy. Information and resources related to the GWAS Policy can be found on this website.
Proper citation: Genomic Datasharing (RRID:SCR_005233) Copy
This resource provides a list of federal program officials in the neurosciences. An informal compendium of names and contact information for nearly 300 research grant and scientific review administrators in 21 organizational units.
Proper citation: NRF Contacts (RRID:SCR_001473) Copy
http://www.nesys.uio.no/Atlas3D/
A multi-platform visualization tool which allows import and visualization of 3-D atlas structures in combination with tomographic and histological image data. The tool allows visualization and analysis of the reconstructed atlas framework, surface modeling and rotation of selected structures, user-defined slicing at any chosen angle, and import of data produced by the user for merging with the atlas framework. Tomographic image data in NIfTI (Neuroimaging Informatics Technology Initiative) file format, VRML and PNG files can be imported and visualized within the atlas framework. XYZ coordinate lists are also supported. Atlases that are available with the tool include mouse brain structures (3-D reconstructed from The Mouse Brain in Stereotaxic Coordinates by Paxinos and Franklin (2001)) and rat brain structures (3-D reconstructed from The Rat Brain in Stereotaxic Coordinates by Paxinos and Watson (2005)). Experimental data can be imported in Atlas3D and warped to atlas space, using manual linear registration, with the possibility to scale, rotate, and position the imported data. This facilitates assignment of location and comparative analysis of signal location in tomographic images.
Proper citation: Atlas3D (RRID:SCR_001808) Copy
A question answer forum for scientists, focusing on methods in bioinformatics, computational genomics and biological data analysis. They welcome detailed and specific posts, written clearly and simply.
Proper citation: BioStar (RRID:SCR_002580) Copy
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