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http://en.wikipedia.org/

Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Its 19 million articles (over 3.6 million in English) have been written collaboratively by volunteers around the world, and almost all of its articles can be edited by anyone with access to the site. As of July 2011, there were editions of Wikipedia in 282 languages. Wikipedia was launched in 2001 by Jimmy Wales and Larry Sanger and has become the largest and most popular general reference work on the Internet, ranking around seventh among all websites on Alexa and having 365 million readers. The name Wikipedia was coined by Larry Sanger and is a combination of wiki (a technology for creating collaborative websites, from the Hawaiian word wiki, meaning quick) and encyclopedia. Wikipedia''s departure from the expert-driven style of encyclopedia building and the large presence of unacademic content has been noted several times. Some have noted the importance of Wikipedia not only as an encyclopedic reference but also as a frequently updated news resource because of how quickly articles about recent events appear. Although the policies of Wikipedia strongly espouse verifiability and a neutral point of view, critics of Wikipedia accuse it of systemic bias and inconsistencies (including undue weight given to popular culture), and allege that it favors consensus over credentials in its editorial processes. Its reliability and accuracy are also targeted. A 2005 investigation in Nature showed that the science articles they compared came close to the level of accuracy of Encyclopedia Britannica and had a similar rate of serious errors.

Proper citation: Wikipedia (RRID:SCR_004897) Copy   

•   Source: SciCrunch Registry

http://www.ibcresearch.org/

The Inflammatory Breast Cancer Research Foundation is a non-profit corporation dedicated to the support of research and public awareness. It is dedicated to researching the cause of Inflammatory Breast Cancer, also known as IBC, an advanced and accelerated form of breast cancer usually not detected by mammograms or ultrasounds. Inflammatory breast cancer requires immediate aggressive treatment with chemotherapy prior to surgery and is treated differently than more common types of breast cancer. Our mission is to assist scientists and researchers in their quest to determine the definitive causes of inflammatory breast cancer. The Inflammatory Breast Cancer Research Foundation seeks to assist them in their work so effective and meaningful detection and diagnosis, prevention and treatment can be pursued and achieved. Our Goals Include: * To ignite interest in the study and research of inflammatory breast cancer at every level. From researchers to physicians, educators and scientists, the IBC Research Foundation seeks to support and inspire those seeking to identify the cause(s) of inflammatory breast cancer. * To support research, the purpose of which is to reach an unambiguous definition of inflammatory breast cancer. The clinical/pathological definition in use since the late 1800s with little change in the 1900s is ambiguous and doesn''t result in a diagnosis of all cases of IBC. By using research methods available in the 21st Century, an unambiguous definition is now possible, assuring with high certainty that all cases of IBC will be correctly diagnosed, and possible sub-types of IBC identified, which may lead to better treatment outcomes. * To increase awareness of IBC for primary care physicians, nursing professionals, and medical technicians in order to minimize the time from presentation of symptoms to correct diagnosis of inflammatory breast cancer. * To increase public awareness in an effort to encourage women to seek medical attention for common inflammatory breast cancer symptoms soon after they appear and to empower patients, caregivers, families and friends to pursue meaningful paths in support of diagnosis and treatment of inflammatory breast cancer.

Proper citation: Inflammatory Breast Cancer Research Foundation (RRID:SCR_004898) Copy   

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http://www.ncbi.nlm.nih.gov/sra

Repository of raw sequencing data from next generation of sequencing platforms including including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, Complete Genomics, and Pacific Biosciences SMRT. In addition to raw sequence data, SRA now stores alignment information in form of read placements on reference sequence. Data submissions are welcome. Archive of high throughput sequencing data,part of international partnership of archives (INSDC) at NCBI, European Bioinformatics Institute and DNA Database of Japan. Data submitted to any of this three organizations are shared among them.

Proper citation: NCBI Sequence Read Archive (SRA) (RRID:SCR_004891) Copy   

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http://www.arb-silva.de/aligner/

Service to align and optionally taxonomically classify your rRNA gene sequences. The results can be combined with any other sequences aligned by SINA or taken from the SILVA databases by concatenation of FASTA files or using the ARB MERGE tool. Note: Submission is currently limited to at most 1000 sequences of at most 6000 bases each. If your requirements exceed this limitation, get Opens internal link in current windowSINA for local installation.

Proper citation: SINA (RRID:SCR_005067) Copy   

•   Source: SciCrunch Registry

http://211.73.64.34/NNG

Neuron Navigator (NNG) integrates a 3D neuron image database into an easy-to-use visual interface. Via a flexible and user-friendly interface, NNG is designed to help researchers analyze and observe the connectivity within the neural maze and discover possible pathways. With NNG''s 3D neuron image database, researchers can perform volumetric searches using the location of neural terminals, or the occupation of neuron volumes within the 3D brain space. Also, the presence of the neurons under a combination of spatial restrictions can be shown as well. NNG is a result of a multi-discipline collaboration between neuroscientists and computer scientists, and NNG has now been implemented on a coordinated brain space for the Drosophila (fruit fly) brain. Account is required.

Proper citation: Neuron Navigator (RRID:SCR_005063) Copy   

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http://seqant.genetics.emory.edu/

A free web service and open source software package that performs rapid, automated annotation of DNA sequence variants (single base mutations, insertions, deletions) discovered with any sequencing platform. Variant sites are characterized with respect to their functional type (Silent, Replacement, 5' UTR, 3' UTR, Intronic, Intergenic), whether they have been previously submitted to dbSNP, and their evolutionary conservation. Annotated variants can be viewed directly on the web browser, downloaded in a tab delimited text file, or directly uploaded in a Browser Extended Data (BED) format to the UCSC genome browser. SeqAnt further identifies all loci harboring two or more coding sequence variants that help investigators identify potential compound heterozygous loci within exome sequencing experiments. In total, SeqAnt resolves a significant bottleneck by allowing an investigator to rapidly prioritize the functional analysis of those variants of interest.

Proper citation: SeqAnt (RRID:SCR_005186) Copy   

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http://clams.jgi-psf.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 2nd, 2023. Sequence composition based classifier for metagenomic sequences. It works by capturing signatures of each sequence based on the sequence composition. Each sequence is modeled as a walk in a de Bruijn graph with underlying Markov chain properties. ClaMS captures stationary parameters of the underlying Markov chain as well as structural parameters of the underlying de Bruijn graph to form this signature. In practice, for each sequence to binned, such a signature is computed and matched to similar signatures computed for the training sets. The best match that also qualifies the normalized distance cut-off wins. In the case that the best match does not qualify this cut-off, the sequence remains un-binned.

Proper citation: Classifier for Metagenomic Sequences (RRID:SCR_004929) Copy   

•   Source: SciCrunch Registry

http://www.methodbox.org/

Collaboration environment for sharing variable sets and statistical methods for analysis across social science survey data. MethodBox enables you to browse and download datasets, share methods and scripts, find fellow researchers with similar interests and share your knowledge. MethodBox source available on Google code. Finding the variables you need to support a particular research question can be time consuming. Wading through hundreds of pages of PDF documents, codebooks and metadata and then trying to find the exact column in a huge spreadsheet can be very frustrating. MethodBox gets you to the variables faster and lets you download only the data you need. You can also share your scripts with others to allow them to adopt best practice quicker than before.

Proper citation: MethodBox (RRID:SCR_004928) Copy   

•   Source: SciCrunch Registry

http://www.anatomyatlases.org/

An anatomy digital health sciences library to educate patients, healthcare providers, and students in a free and anonymous manner while using current, authoritative, trustworthy health information. Anatomy Atlases addresses the continuum of anatomy education and may be of use primarily to three distinct populations. It is written for and intended primarily for use by Medical Students, Residents, Fellows, or Attending Physicians studying anatomy. Other Health Care Providers studying anatomy should find it useful. Finally, Patients (including patient''s family members or friends) may find it helpful. Anatomy Textbooks and Anatomy Atlases: * Atlas of Human Anatomy * Atlas of Human Anatomy in Cross Section * Illustrated Encyclopedia of Human Anatomic Variation * Atlas of Microscopic Anatomy - A Functional Approach: Companion to Histology and Neuroanatomy: Second Edition * Anatomy of First Aid - A Case Study Approach * Lessons From a Bone Box Lessons From a Bone Box

Proper citation: Anatomy Atlases (RRID:SCR_004888) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.knowledgeblog.org/

Series of tutorial material covering a broad selection of topics in bioinformatics. Categories include: Bioinformatics APIs, Data integration, Events, Grid and Cloud Computing, Metabolic modelling, Reviews, Software Comparisons, Statistics, Systems Biology, Transcriptomics, Tutorials.

Proper citation: Bioinformatics Knowledgeblog (RRID:SCR_005379) Copy   

•   Source: SciCrunch Registry

http://compbio.cs.brown.edu/projects/gasv/

Software tool combining both paired read and read depth signals into probabilistic model which can analyze multiple alignments of reads. Used to find structural variation in both normal and cancer genomes using data from variety of next-generation sequencing platforms. Used to predict structural variants directly from aligned reads in SAM/BAM format.Combines read depth information along with discordant paired read mappings into single probabilistic model two common signals of structural variation. When multiple alignments of read are given, GASVPro utilizes Markov Chain Monte Carlo procedure to sample over the space of possible alignments.

Proper citation: GASVPro (RRID:SCR_005259) Copy   

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http://headit.ucsd.edu

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

Proper citation: HeadIT (RRID:SCR_005657) Copy   

•   Source: SciCrunch Registry

http://bejerano.stanford.edu/prism/public/html/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRISM (Stanford database) (RRID:SCR_005375) Copy   

•   Source: SciCrunch Registry

http://brainethics.org/

There are a lot of fine blogs out there covering the avalance of current neuroscience research. With this blog Thomas Rams��y & Martin Skov want to highlight the many consequences of this growing understanding of the human brain. We are especially interested in two types of consequences: Tinkering with the brain and What is it like to be a human being? * Tinkering with the brain: First and foremost, with an understanding of how the brain works comes the possibility of tinkering with it. We already use billions of dollars every year on psychopharmocologia trying to treat depression, schizophrenia, obsessive-compulsive disorder and other mental diseases. But should we also use our knowledge of the brain to treat undesirable mental traits such as pedophilia or sociopathy? And what about enhancing normal brains? Clearly, evolution hasn''t endowed us with the most efficient brain imaginable. Shouldn''t we do something about its many shortcomings? * What is it like to be a human being?: Secondly, our view of human behavior is sure to change with our improved understanding of the human brain. Our knowledge of core human faculties such as language, social reasoning, aesthetics, and economics is already being challenged by modern neuroscience, yielding multiple hard questions. Do we have a free will? Is the mind innate or plastic? If people are not responsible for their actions (since all actions are caused by blind molecular processes) does our legal system still make sense? In short, will modern neuroscience come to completely redefine human nature? We try to discuss contemporary research literature, not just news reports. Although we will occasionally also target popular science reports, since we believe they play an important role in dissemining lessons from the lab. And in the future we plan to also post interviews with interesting researchers, as well as link to our own publications in journals and books. Additionally, the latest and most important books in the multidisciplinary field of neuroscience, cognition, psychology, ethics and economics are presented.

Proper citation: BrainEthics (RRID:SCR_005530) Copy   

•   Source: SciCrunch Registry

http://www.pazar.info/

Database that unites independently created and maintained data collections of transcription factor and regulatory sequence annotation. The flexible PAZAR schema permits the representation of diverse information derived from experiments ranging from biochemical protein-DNA binding to cellular reporter gene assays. Data collections can be made available to the public, or restricted to specific system users. The data ''boutiques'' within the shopping-mall-inspired system facilitate the analysis of genomics data and the creation of predictive models of gene regulation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PAZAR (RRID:SCR_005410) Copy   

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http://mcb.berkeley.edu/labs/werblin/index.html

The goal of our research is to uncover the neural circuitry that mediates some of the remarkable processing capabilities of the retina. The retina to operates at high spatial and temporal resolution over more than 7 orders of magnitude, to detect the direction of motion, to blank and then recover after saccades, to generate at least a dozen different abstract representations of the visual world. How is all of this, and much more, possible in this tissuepaper-thin array of neurons? Videos and images describing this include: * The retinal hypercircuit. * How the Retina Works * Take a Tour through the Retina * Cartoon of the retina showing layering of neurons * Directional Selectivity * Feedback and Crossover inhibition * Multiple Representations of the Visual Scene ** Pseudo Array Recording Methods ** Multiple Representations of the Visual World ** Regions of Frequency Space * Regions of space/time frequency * Space-time rasters for ON and OFF cells * Patching a neuron in a retinal slice * Targeting Retinal Neuron Subregions with Arficial Rhodopsins

Proper citation: Werblin Lab (RRID:SCR_005251) Copy   

•   Source: SciCrunch Registry

https://kepler-project.org/

Kepler is a software application for analyzing and modeling scientific data. Using Kepler''s graphical interface and components, scientists with little background in computer science can create executable models, called scientific workflows, for flexibly accessing scientific data (streaming sensor data, medical and satellite images, simulation output, observational data, etc.) and executing complex analyses on this data. Kepler is developed by a cross-project collaboration led by the Kepler/CORE team. The software builds upon the mature Ptolemy II framework, developed at the University of California, Berkeley. Ptolemy II is a software framework designed for modeling, design, and simulation of concurrent, real-time, embedded systems. The Kepler Project is dedicated to furthering and supporting the capabilities, use, and awareness of the free and open source, scientific workflow application, Kepler. Kepler is designed to help scien��tists, analysts, and computer programmers create, execute, and share models and analyses across a broad range of scientific and engineering disciplines. Kepler can operate on data stored in a variety of formats, locally and over the internet, and is an effective environment for integrating disparate software components, such as merging R scripts with compiled C code, or facilitating remote, distributed execution of models. Using Kepler''s graphical user interface, users simply select and then connect pertinent analytical components and data sources to create a scientific workflowan executable representation of the steps required to generate results. The Kepler software helps users share and reuse data, workflows, and compo��nents developed by the scientific community to address common needs. Kepler is a java-based application that is maintained for the Windows, OSX, and Linux operating systems. The Kepler Project supports the official code-base for Kepler development, as well as provides materials and mechanisms for learning how to use Kepler, sharing experiences with other workflow developers, reporting bugs, suggesting enhancements, etc. The Kepler Project Leadership Team works to assure the long-term technical and financial viability of Kepler by making strategic decisions on behalf of the Kepler user community, as well as providing an official and durable point-of-contact to articulate and represent the interests of the Kepler Project and the Kepler software application. Details about how to get more involved with the Kepler Project can be found in the developer section of this website.

Proper citation: Kepler (RRID:SCR_005252) Copy   

•   Source: SciCrunch Registry

https://cgwb.nci.nih.gov/goldenPath/bamview/documentation/index.html

A variant detector and graphical alignment viewer for next-generation sequencing data in the SAM/BAM format, which is capable of pooling data from multiple source files. Bambino may be launched online via Java Web Start or downloaded and run locally.

Proper citation: Bambino (RRID:SCR_005649) Copy   

•   Source: SciCrunch Registry

http://neurolex.org/wiki/Main_Page

A freely editable semantic wiki for community-based curation of the terms used in Neuroscience. Entries are curated and eventually incorporated into the formal NIFSTD ontology. NeuroLex also includes a Resource branch for community members to freely add neuroscience relevant resources that do not become part of NIFSTD ontology but rather make up the NIF Registry. As part of the NIF, we provide a simple search interface to many different sources of neuroscience information and data. To make this search more effective, we are constructing ontologies to help organize neuroscience concepts into category hierarchies, e.g., neuron is a cell. These categories provide the means to perform more effective searches and also to organize and understand the information that is returned. But an important adjunct to this activity is to clearly define all of the terms that we use to describe our data, e.g., anatomical terms, techniques, organism names. Because wikis provide an easy interface for communities to contribute their knowledge, we started the NeuroLex.

Proper citation: NeuroLex (RRID:SCR_005402) Copy   

•   Source: SciCrunch Registry

http://www.gene-regulation.com/pub/databases.html#transpath

Database on eukaryotic transcription factors, their experimentally-proven binding sites, consensus binding sequences (positional weight matrices) and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. It can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyzer. Cross-references to important sequence and signature databases such as EMBL/GenBank UniProt/Swiss-Prot InterPro or Ensembl EntrezGene RefSeq are provided. The database is equipped with the tools for data visualization and analysis. It has three modules: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence facilitates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes.

Proper citation: TRANSPATH (RRID:SCR_005640) Copy   

•   Source: SciCrunch Registry