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http://www.biostars.org/

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   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/RAD

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on March 24, 2014. A resource for gene expression studies, storing highly curated MIAME-compliant studies (i.e. experiments) employing a variety of technologies such as filter arrays, 2-channel microarrays, Affymetrix chips, SAGE, MPSS and RT-PCR. Data were available for querying and downloading based on the MGED ontology, publications or genes. Both public and private studies (the latter viewable only by users having appropriate logins and permissions) were available from this website. Specific details on protocols, biomaterials, study designs, etc., are collected through a user-friendly suite of web annotation forms. Software has been developed to generate MAGE-ML documents to enable easy export of studies stored in RAD to any other database accepting data in this format. RAD is part of a more general Genomics Unified Schema (http://gusdb.org), which includes a richly annotated gene index (http://allgenes.org), thus providing a platform that integrates genomic and transcriptomic data from multiple organisms. NOTE: Due to changes in technology and funding, the RAD website is no longer available. RAD as a schema is still very much active and incorporated in the GUS (Genomics Unified Schema) database system used by CBIL (EuPathDB, Beta Cell Genomics) and others. The schema for RAD can be viewed along with the other GUS namespaces through our Schema Browser.

Proper citation: RNA Abundance Database (RRID:SCR_002771) Copy   

•   Source: SciCrunch Registry

http://www.credrivermice.org/

Project to provide Neuroscience Community with mouse strains that are suitable for tissue and cell-type-specific perturbation of gene function in nervous system. NIH Neuroscience Blueprint has established three centers in the USA for generation of genetically modified mice expressing CRE recombinases in nervous system on the C57BJ/6 genetic background. Mouse lines are generated at Cold Spring Harbor Lab, at Scripps Research Institute, and at Baylor College of Medicine.

Proper citation: CRE Driver Network (RRID:SCR_002720) Copy   

•   Source: SciCrunch Registry

http://www.mybiosoftware.com/population-genetics/332

A tool for SNP Search and downloading with local management. It also offers flanking sequence downloading and automatic SNP filtering. It requires Windows and .NET Framework.

Proper citation: SNPHunter (RRID:SCR_002968) Copy   

•   Source: SciCrunch Registry

http://insitu.fruitfly.org/cgi-bin/ex/insitu.pl

Database of embryonic expression patterns using a high throughput RNA in situ hybridization of the protein-coding genes identified in the Drosophila melanogaster genome with images and controlled vocabulary annotations. At the end of production pipeline gene expression patterns are documented by taking a large number of digital images of individual embryos. The quality and identity of the captured image data are verified by independently derived microarray time-course analysis of gene expression using Affymetrix GeneChip technology. Gene expression patterns are annotated with controlled vocabulary for developmental anatomy of Drosophila embryogenesis. Image, microarray and annotation data are stored in a modified version of Gene Ontology database and the entire dataset is available on the web in browsable and searchable form or MySQL dump can be downloaded. So far, they have examined expression of 7507 genes and documented them with 111184 digital photographs.

Proper citation: Patterns of Gene Expression in Drosophila Embryogenesis (RRID:SCR_002868) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/

Data archive of more than 500,000 files of research in the social sciences, hosting 16 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields. ICPSR comprises a consortium of about 700 academic institutions and research organizations providing training in data access, curation, and methods of analysis for the social science research community. ICPSR welcomes and encourages deposits of digital data. ICPSR's educational activities include the Summer Program in Quantitative Methods of Social Research external link, a comprehensive curriculum of intensive courses in research design, statistics, data analysis, and social methodology. ICPSR also leads several initiatives that encourage use of data in teaching, particularly for undergraduate instruction. ICPSR-sponsored research focuses on the emerging challenges of digital curation and data science. ICPSR researchers also examine substantive issues related to our collections, with an emphasis on historical demography and the environment.

Proper citation: Inter-university Consortium for Political and Social Research (ICPSR) (RRID:SCR_003194) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://slicer.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

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   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.zebrafinch.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Project to advance understanding of the neural mechanisms of vocal learning by providing a quantitative description of the relationship between physiological variables and vocal performance over the course of development in a songbird, the zebra finch. They propose to study vocal learning dynamically across neuronal and peripheral subsystems, using a novel collaborative approach that will harness the combined expertise of several investigators. Their proposed research model will 1) provide simultaneous measurements of acoustic, articulatory and electrophysiological data that will document the detailed dynamics of the vocal imitation process in a standardized learning paradigm; and 2) incorporate these measurements into a theoretical/computational framework that simultaneously provides a phenomenological description and attempts to elucidate the mechanistic basis of the learning process.

Proper citation: Zebra Finch Song Learning Consortium (RRID:SCR_006356) Copy   

•   Source: SciCrunch Registry

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

Repository for electron microscopy density maps of macromolecular complexes and subcellular structures at Protein Data Bank in Europe. Covers techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.

Proper citation: Electron Microscopy Data Bank at PDBe (MSD-EBI) (RRID:SCR_006506) Copy   

•   Source: SciCrunch Registry

http://grants.nih.gov/grants/oer.htm

OER serves as a vital interface between the NIH and the biomedical research community by guiding investigators through the process of attaining grants funding and helping them understand and navigate through federal policies and procedures. OER supports extramural research by providing policy and guidance to the 24 NIH Institutes and Centers that award grants. Extramural grants account for approximately 84 percent of NIH''s 29 billion budget. These are awarded to investigators throughout the U.S. and abroad. Approximately 10 percent of the NIH budget supports NIH intramural investigators, NIH staff who conduct research.

Proper citation: Office of Extramural Research NIH (RRID:SCR_006547) Copy   

•   Source: SciCrunch Registry

http://www.medschool.lsuhsc.edu/neuroscience/

Research center that takes multidisciplinary approach to neuroscience education and research. Research programs on molecular and cellular bases of neural diseases are the center of the innovative educational programs. Primary mission is to foster and conduct science that advances understanding of brain function and diseases that affect nervous system.

Proper citation: Louisiana State University School of Medicine Neurosciences Center (RRID:SCR_006446) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/

Consortium that puts sequences into a chromosome context and provides the best possible reference assembly for human, mouse, and zebrafish via FTP. Tools to facilitate the curation of genome assemblies based on the sequence overlaps of long, high quality sequences.

Proper citation: Genome Reference Consortium (RRID:SCR_006553) Copy   

•   Source: SciCrunch Registry

https://wiki.nci.nih.gov/display/LexEVS/LexGrid

LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: LexGrid (RRID:SCR_006627) Copy   

•   Source: SciCrunch Registry