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http://www.thebiogrid.org/

Curated protein-protein and genetic interaction repository of raw protein and genetic interactions from major model organism species, with data compiled through comprehensive curation efforts.

Proper citation: Biological General Repository for Interaction Datasets (BioGRID) (RRID:SCR_007393) Copy   

•   Source: SciCrunch Registry

http://cor.physiol.ox.ac.uk/

Cellular Open Resource is a Microsoft Windows environment for cellular modeling that is built around CellML (except for reactions and metadata which are not supported). It offers, through CellML, an ''out of the box'' access to a large database of single cell models. COR was among the early adopters of this standard, eventually forming the first publicly available CellML-based modeling and collaboration environment. From the onset, COR was designed to provide an environment that could not only be used by experienced modelers, but also by experimentalists, teachers and students. It therefore tries to combine a user-friendly interface with a computationally efficient numerical engine. In this paper, we introduce the philosophy behind COR, explain its user interface and current functionality, including the editing and running of CellML files, highlight lessons learned from user feedback and problems experienced during the development of COR and conclude by exploring future development potential. Sponsors: This study has been supported by a grant from the UK Biotechnology and Biological Sciences Research Council (BB/E024955/1). Keyword: Cell, Model, Cellular, Modeling, Open resource, Microsoft, Environment, Database, Experimentalist, Teacher, Student, Modeler, Computationally, Development,

Proper citation: Cellular Open Resource (RRID:SCR_008022) Copy   

•   Source: SciCrunch Registry

http://www.reciprocalnet.org/

Database of crystallographic information. Its membership includes crystallographic service facilities (that analyze crystals submitted by research chemists) located at major universities. These labs analyze anywhere from a few dozen to several hundred molecular structures each year and post the data online for the public to access. A distributed database engine takes care of shuttling this data across the Internet so that every structure can be located by the search engine. There may be a delay of a year or more between the time a structure is first analyzed and the time it finally becomes available for the public to see. This is due to intellectual property issues - the intervening time allows the chemists who first discovered the structure to publish it in a trade journal.

Proper citation: Reciprocal Net (RRID:SCR_008238) Copy   

•   Source: SciCrunch Registry

http://www.flymine.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Integrated database of genomic, expression and protein data for Drosophila, Anopheles, C. elegans and other organisms. You can run flexible queries, export results and analyze lists of data. FlyMine presents data in categories, with each providing information on a particular type of data (for example Gene Expression or Protein Interactions). Template queries, as well as the QueryBuilder itself, allow you to perform searches that span data from more than one category. Advanced users can use a flexible query interface to construct their own data mining queries across the multiple integrated data sources, to modify existing template queries or to create your own template queries. Access our FlyMine data via our Application Programming Interface (API). We provide client libraries in the following languages: Perl, Python, Ruby and & Java API

Proper citation: FlyMine (RRID:SCR_002694) Copy   

•   Source: SciCrunch Registry

http://studyforrest.org

An MRI data repository that holds a set of 7 Tesla images and behavioral metadata. Multi-faceted brain image archive with behavioral measurements. For each participant a number of different scans and auxiliary recordings have been obtained. In addition, several types of minimally preprocessed data are also provided. The full description of the data release is available in a dedicated publication. This project invites anyone to participate in a decentralized effort to explore the opportunities of open science in neuroimaging by documenting how much (scientific) value can be generated out of a single data release by publication of scientific findings derived from a dataset, algorithms and methods evaluated on this dataset, and/or extensions of this dataset by acquisition and integration of new data.

Proper citation: studyforrest.org (RRID:SCR_003112) Copy   

•   Source: SciCrunch Registry

http://www.morphobank.org

Web application providing online database and workspace for evolutionary research, specifically systematics (the science of determining the evolutionary relationships among species). It enables researchers to upload images and affiliate data with those images (labels, species names, etc.) and allows researchers to upload morphological data and affiliate it with phylogenetic matrices. MorphoBank is project-based, meaning a team of researchers can create a project and share the images and associated data exclusively with each other. When a paper associated with the project is published, the research team can make their data permanently available for view on MorphoBank where it is now archived.

Proper citation: MorphoBank (RRID:SCR_003213) Copy   

•   Source: SciCrunch Registry

http://dkcoin.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented October 13, 2014. The resource has moved to the NIDDKInformation Network (dkNET) project. Contact them at info_at_dknet.org with any questions. Database of large pools of data relevant to the mission of NIDDKwith the goal of developing a community-based network for integration across disciplines to include the larger DKuniverse of diseases, investigators, and potential users. The focus is on greater use of this data with the objective of adding value by breaking down barriers between sites to facilitate linking of different datasets. To date (2013/06/10), a total of 1,195 resources have been associated with one or more genes. Of 11,580 total genes associated with resources, the ten most represented are associated with 359 distinct resources. The main method by which they currently interconnect resources between the providers is via EntrezGene identifiers. A total of 780 unique genes provide the connectivity between 3,159 resource pairs across consortia. To further increase interconnectivity, the groups have been further annotating their data with additional gene identifiers, publications, and ontology terms from selected Open Biological and Biomedical Ontologies (OBO).

Proper citation: dkCOIN (RRID:SCR_004438) Copy   

•   Source: SciCrunch Registry

http://proteome.gs.washington.edu/software/bibliospec/documentation/index.html

BiblioSpec enables the identification of peptides from tandem mass spectra by searching against a database of previously identified spectra. This suite of software tools is for creating and searching MS/MS peptide spectrum libraries. BiblioSpec is available free of charge for noncommercial use through an interactive web-site at http://depts.washington.edu/ventures/UW_Technology/Express_Licenses/bibliospec.php The BiblioSpec package contains the following programs: * BlibBuild creates a library of peptide MS/MS spectra from MS2 files. * BlibFilter removes redundant spectra from a library. * BlibSearch searches a spectrum library for matches to query spectra, reporting the results in an SQT file. In addition to the primary programs, the following auxiliary programs are available: * BlibStats writes summary statistics describing a library. * BlibToMS2 writes a library in MS2 file format. * BlibUpdate adds, deletes, or annotates spectra. * BlibPpMS2 processes spectra (bins peaks, removes noise, normalizes intensity) as done in BlibSearch and prints the resulting spectra to a text file. Several reference libraries are available for download. These libraries are updated regularly and are for use under the Linux operating system. You will find libraries for * Escherichia coli * Saccharomyces cerevisiae * Caenorhabditis elegans

Proper citation: BiblioSpec (RRID:SCR_004349) Copy   

•   Source: SciCrunch Registry

http://kingdevicktest.com/

An accurate and reliable method for identifying athletes with head trauma, and a strong candidate rapid sideline screening test for concussion. The test is able to capture impairments of eye movement, attention, language and other symptoms of impaired brain function. It is a physical method of evaluating visual tracking and saccadic eye movements is based on the time to perform rapid number naming. It involves reading aloud a series of single digit numbers from left to right on three test cards. Participants are asked to read the numbers on each card from left to right as quickly as possible but without making any errors. The sum of the three test card time scores constitutes the summary score for the entire test. The test is a proven indicator of oculomotor inefficiencies regarding eye movements during reading. Published medical studies have determined that deficiencies in saccadic eye movements can be an indicator of mild Traumatic Brain Injury (mTBI) or concussions. Studies have shown that there is a significant relationship between poor oculomotor functions and learning disabilities (including dyslexia detection). Saccadic eye movement deficiencies can be improved with training and correspondingly reading performance also can be improved. Simply put, subjects who don''t perform well on this test are not efficient readers, although because there are many reasons for poor reading unrelated to eye movements, some poor readers do fine on the test. They believe that the test should be in the hands of teachers in order to help them determine if a student''s poor reading performance is related to deficiencies in their ability to move their eyes efficiently.

Proper citation: King-Devick Test (RRID:SCR_004500) Copy   

•   Source: SciCrunch Registry

http://www.doaj.org/

Database providing access to quality controlled Open Access Journals. For a journal to be included it should exercise quality control on submitted papers through an editor, editorial board and/or a peer-review system. It is not be limited to particular languages or subject areas. Offering free online access to high quality full text content, plus excellent search tools, the portal enables researchers to find, use and re-use a vast range of materials with ease. The content of DOAJ will be even more visible and disseminated through this portal. The aim of the Directory is to increase the visibility and ease of use of open access scientific and scholarly journals thereby promoting their increased usage and impact. As of April 2014, DOAJ has 9,709 journals, 5,624 journals searchable at article level, 133 Countries and 1,600,991 articles. The database may be browsed by title or subject, or searched through the interface to for journals or articles.

Proper citation: DOAJ - Directory of Open Access Journals (RRID:SCR_004521) Copy   

•   Source: SciCrunch Registry

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

Percolator post-processes the results of a shotgun proteomics database search program, re-ranking peptide-spectrum matches so that the top of the list is enriched for correct matches. Shotgun proteomics uses liquid chromatography-tandem mass spectrometry to identify proteins in complex biological samples. We describe an algorithm, called Percolator, for improving the rate of peptide identifications from a collection of tandem mass spectra. Percolator uses semi-supervised machine learning to discriminate between correct and decoy spectrum identifications, correctly assigning peptides to 17% more spectra from a tryptic dataset and up to 77% more spectra from non-tryptic digests, relative to a fully supervised approach. The yeast-01 data is available in tab delimetered format. The SEQUEST parameter file and target database for the yeast and worm data are also available.

Proper citation: Percolator: Semi-supervised learning for peptide identification from shotgun proteomics datasets (RRID:SCR_005040) Copy   

•   Source: SciCrunch Registry

http://toolkit.tuebingen.mpg.de/hhpred

The primary aim in developing HHpred was to provide biologists with a method for sequence database searching and structure prediction that is as easy to use as BLAST or PSI-BLAST and that is at the same time much more sensitive in finding remote homologs. In fact, HHpred''s sensitivity is competitive with the most powerful servers for structure prediction currently available. HHpred is the first server that is based on the pairwise comparison of profile hidden Markov models (HMMs). Whereas most conventional sequence search methods search sequence databases such as UniProt or the NR, HHpred searches alignment databases, like Pfam or SMART. This greatly simplifies the list of hits to a number of sequence families instead of a clutter of single sequences. All major publicly available profile and alignment databases are available through HHpred.

Proper citation: HHpred (RRID:SCR_010276) Copy   

•   Source: SciCrunch Registry

http://dictybase.org/teaching_tools/index.html

Dictyostelium discoideum is a great organism to use to teach cellular biology. It exhibits very interesting behaviors, such as chemotaxis and phagocytosis, that can readily be studied in standard laboratories without the need for expensive equipment. Lists of labs being used in real courses settings and all necessary information for performing those experiments are provided. Major headings: * Dictyostelium cell biology course, by Dr. David Knecht, University of Connecticut * Dictyostelium cell biology, by Dr. Derrick Brazill, Hunter College, New York * Report on the number of cells in a slug, contributed by John Bonner * Practical on chemotaxis, by Dr. Thierry Soldati, University of Geneva * Comments from Researchers * References suggested by contributors

Proper citation: dictyBase - Teaching Tools Using Dictyostelium discoideum (RRID:SCR_010701) Copy   

•   Source: SciCrunch Registry

http://compgenomics.utsa.edu/gene/gene_1.php

A Bayesian decision fusion algorithm for microRNA target prediction that combines the prediction of TargetScan, miRanda, PicTar, mirTarget, PITA, and DianamicroT. Users enter a Ref_seq ID for a query target gene and select a miRNA, which BCmicrO will use in its predictive algorithm. The prediction results can then be downloaded.

Proper citation: BCmicrO (RRID:SCR_010838) Copy   

•   Source: SciCrunch Registry

http://mutpred.mutdb.org/

Web application tool developed to classify an amino acid substitution as disease-associated or neutral in human.

Proper citation: MutPred (RRID:SCR_010778) Copy   

•   Source: SciCrunch Registry

http://www.epilepsygenetics.eu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Group of clinical care and epilepsy research centers who are committed to improving the lives of people with epilepsy through an understanding of the genetics of epilepsy. The consoritum was in an effort to speed discovery to epilepsy genetics by pooling the resources of several research centres., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EPIGEN (RRID:SCR_000093) Copy   

•   Source: SciCrunch Registry

http://discover.nci.nih.gov/gominer/GoCommandWebInterface.jsp

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A web program that organizes lists of genes of interest (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology and automates the analysis of multiple microarrays then integrates the results across all of them in exportable output files and visualizations. High-Throughput GoMiner is an enhancement of GoMiner and is implemented with both a command line interface and a web interface. The program can also: efficiently perform automated batch processing of an arbitrary number of microarrays; produce a human- or computer-readable report that rank-orders the multiple microarray results according to the number of significant GO categories; integrate the multiple microarray results by providing organized, global clustered image map visualizations of the relationships of significant GO categories; provide a fast form of false discovery rate multiple comparisons calculation; and provide annotations and visualizations for relating transcription factor binding sites to genes and GO categories.

Proper citation: High-Throughput GoMiner (RRID:SCR_000173) Copy   

•   Source: SciCrunch Registry

http://swordapp.github.io/SWORDv2-Profile/SWORDProfile.html#introduction

A software that is used for the management of data and to deposit content between different locations. A request from an authenticated user is sent to implement for the "service document", which returns details of the collection that user is allowed to deposit within the repository. At this point, the user can deposit their file into a collection, which can then be accessed at a different location.

Proper citation: SWORD (RRID:SCR_000593) Copy   

•   Source: SciCrunch Registry

https://iscconsortium.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Consortium to advance the understanding of intestinal epithelial stem cell biology during development, homeostasis, regeneration and disease. Its immediate goals are to isolate, characterize, culture and validate populations of intestinal stem cells; answer major questions in stem cell biology of the intestinal epithelium; and accelerate research by making information and resources available to the research community. Resources include data sets, protocols, and a resource catalog. Long-term goals include: 1) laying the ground work for therapeutic manipulation of the intestinal epithelium 2) contributing to the greater understanding of stem cell biology through knowledge of the intestine as a model stem cell-driven system. Research Projects are housed at 8 institutions across the nation: Oregon Health & Science University, Stanford University, Stowers Institute for Medical Research, University of California, Los Angeles School of Medicine (UCLA) (partnered with the VA Greater Los Angeles), University of North Carolina, Chapel Hill (UNC), University of Oklahoma, University of Pennsylvania, and University of Pittsburgh.

Proper citation: Intestinal Stem Cell Consortium (RRID:SCR_001555) Copy   

•   Source: SciCrunch Registry

http://www.opencolleges.edu.au/informed/learning-strategies/

Interactive infographic of a brain exploring more than 100,000 chemical reactions, highlighted by areas and explanations of what that area is known to do.

Proper citation: Open Colleges Interactive Brain (RRID:SCR_001427) Copy   

•   Source: SciCrunch Registry