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http://www.icn.ucl.ac.uk/motorcontrol/

Using robotic devices to investigate human motor behavior, this group develops computational models to understand the underlying control and learning processes. By simulating novel objects or dynamic environments they study how the brain recalibrates well-learned motor skills or acquires new ones. These insights are used to design fMRI studies to investigate how these processes map onto the brain. They have developed a number of novel techniques of how to study motor control in the MRI environment, and how to analyze MRI data of the human cerebellum. They also study patients with stroke or neurological disease to further determine how the brain manages to control the body.

Proper citation: UCL Motor Control Group (RRID:SCR_005271) Copy   

•   Source: SciCrunch Registry

http://www.genes2cognition.org/resources/

Biological resources, including gene-targeting vectors, ES cell lines, antibodies, and transgenic mice, generated for its phenotyping pipeline as part of the Genes to Cognition research program are freely-available to interested researchers. Available Transgenic Mouse Lines: *Hras1 (H-ras) knockout,C57BL/6J *Dlg4 (PSD-95) knockout,129S5 *Dlg4 (PSD-95) knockout,C57BL/6J *Dlg3 (SAP102) knockout with hprt mutation,129S5 *Dlg3 (SAP102) knockout (wild-type for hprt,C57BL/6J *Syngap1 (SynGAP) knockout (from 8.24 clone), C57BL/6J *Dlg4 (PSD-95) guanylate kinase domain deletion, C57BL/6J *Ptk2 (FAK) knockout,C57BL/6J

Proper citation: Genes to Cognition - Biological Resources (RRID:SCR_001675) Copy   

•   Source: SciCrunch Registry

http://flybrain.stanford.edu/

Project content including raw image data, neuronal tracings, image registration tools and analysis scripts covering three manuscripts: Comprehensive Maps of DrosophilaHigher Olfactory Centres : Spatially Segregated Fruit and Pheromone Representation which uses single cell labeling and image registration to describe the organization of the higher olfactory centers of Drosophila; Diversity and wiring variability of olfactory local interneurons in the Drosophila antennal lobe which uses single cell labeling to describe the organization of the antennal lobe local interneurons; and Sexual Dimorphism in the Fly Brain which uses clonal analysis and image registration to identify a large number of sex differences in the brain and VNC of Drosophila. Data * Raw Data of Reference Brain (pic, amira) (both seed and average) * Label field of LH and MB calyx and surfaces for these structures * Label field of neuropil of Reference Brain * Traces (before and after registration). Neurolucida, SWC and AmiraMesh lineset. * MB and LH Density Data for different classes of neuron. In R format and as separate amira files. * Registration files for all brains used in the study * MBLH confocal images for all brains actually used in the study (Biorad pic format) * Sample confocal images for antennal lobe of every PN class * Confocal stacks of GABA stained ventral PNs Programs * ImageJ plugins (Biorad reader /writer/Amira reader/writer/IGS raw Reader) * Binary of registration, warp and gregxform (macosx only, others on request) * Simple GUI for registration tools (macosx only at present) * R analysis/visualization functions * Amira Script to show examples of neuronal classes The website is a collaboration between the labs of Greg Jefferis and Liqun Luo and has been built by Chris Potter and Greg Jefferis. The core Image Registration tools were created by Torsten Rohlfing and Calvin Maurer.

Proper citation: Flybrain at Stanford (RRID:SCR_001877) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

•   Source: SciCrunch Registry

http://www.openmicroscopy.org/site/support/ome-model/ome-tiff/

A standardized file format for multidimensional microscopy image data. OME-TIFF maximizes the respective strengths of OME-XML and TIFF. It takes advantage of the rich metadata defined in OME-XML while retaining the pixel structure in multi-page TIF format for compatibility with many image-processing applications. An OME-TIFF dataset has the following characteristics: * Image planes are stored within one multi-page TIFF file, or across multiple TIFF files. Any image organization is feasible. * A complete OME-XML metadata block describing the dataset is embedded in each TIFF file's header. Thus, even if some of the TIFF files in a dataset are misplaced, the metadata remains intact. * The OME-XML metadata block may contain anything allowed in a standard OME-XML file. * OME-TIFF uses the standard TIFF mechanism for storing one or more image planes in each of the constituent files, instead of encoding pixels as base64 chunks within the XML. Since TIFF is an image format, it makes sense to only use OME-TIFF as opposed to OME-XML, when there is at least one image plane.

Proper citation: OME-TIFF Format (RRID:SCR_002636) Copy   

•   Source: SciCrunch Registry

https://www.openmicroscopy.org/site/products/bio-formats

Standalone software Java library for reading microscopy image data files in any format and writing image data using standardized, open formats. It currently reads and converts more than 120 file formats to the OME-TIFF data standard.

Proper citation: Bio-Formats (RRID:SCR_000450) Copy   

•   Source: SciCrunch Registry

http://zebrafishucl.org/zebrafishbrain#about-1

Collates and curates neuroanatomical data and information generated both in-house and by community to communicate current state of knowledge about neuroanatomical structures in developing zebrafish. Most of data come from high resolution confocal imaging of intact brains in which neuroanatomical structures are labelled by combinations of transgenes and antibodies. Community repository for image based data related to neuroanatomy of zebrafish.

Proper citation: Zebrafish Brain Atlas (RRID:SCR_000606) Copy   

•   Source: SciCrunch Registry

https://github.com/shanemomara/omaraneurolab/tree/master/NeuroChaT

Software open source python toolbox to analyse neuronal signals recorded in vivo in freely behaving animal, with particular emphasis on spatial coding. Can be used as application programming interface, or as general user interface, and is designed to help simplify adoption of standardised analyses for behavioural neurophysiology and facilitate open data sharing and collaboration between laboratories.

Proper citation: NeuroChaT (RRID:SCR_018020) Copy   

•   Source: SciCrunch Registry

https://www.rappsilberlab.org/software/xisearch/

Software and algorithm for analyzing protein protein cross linking mass spectrometry data. Library of routines for peptide based mass spectrometry. Contains search engine for identification of crosslinked peptides.

Proper citation: xiSEARCH (RRID:SCR_018395) Copy   

•   Source: SciCrunch Registry

http://web.cbio.uct.ac.za/~darren/rdp.html

Software package to analyse nucleotide sequence data and identify evidence of genetic recombination. RDP3 is version of RDP program for characterizing recombination events in DNA-sequence alignments. RDP4 is version of RDP program for detection and analysis of recombination patterns in virus genomes.

Proper citation: Recombination Detection Program (RRID:SCR_018537) Copy   

•   Source: SciCrunch Registry

https://bioweb.pasteur.fr/packages/pack@[email protected]

Open source software tool for analysing trace files generated by Bayesian MCMC runs. Software package for visualising and analysing MCMC trace files generated through Bayesian phylogenetic inference. Provides kernel density estimation, multivariate visualisation, demographic trajectory reconstruction, conditional posterior distribution summary and more.

Proper citation: Tracer (RRID:SCR_019121) Copy   

•   Source: SciCrunch Registry

https://github.com/MetaCell/nwb-explorer

Web application and standalone application to read, visualize and explore content of NWB:N 2 files.Used to share neurophysiological data in Neurodata Without Borders format.

Proper citation: NWB Explorer (RRID:SCR_021151) Copy   

•   Source: SciCrunch Registry

https://spikeinterface.readthedocs.io

Software tool as unified framework for spike sorting. Python framework to unify preexisting spike sorting technologies into single codebase and to facilitate straightforward comparison and adoption of different approaches.Used to reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs.

Proper citation: SpikeInterface (RRID:SCR_021150) Copy   

•   Source: SciCrunch Registry

http://www.cellml.org/models

Repository of biological models created using CellML, a free, open-source, eXtensible markup language based standard for defining mathematical models of cellular function. Models may be browsed by category, which include: Calcium Dynamics, Cardiovascular Circulation, Cell Cycle, Cell Migration, Circadian Rhythms, Electrophysiology, Endocrine, Excitation-Contraction Coupling, Gene Regulation, Hepatology, Immunology, Ion Transport, Mechanical Constitutive Laws, Metabolism, Myofilament Mechanics, Neurobiology, pH Regulation, PKPD, Signal Transduction, Synthetic Biology. The community can contribute their models to this resource.

Proper citation: CellML Model Repository (RRID:SCR_008113) Copy   

•   Source: SciCrunch Registry

http://www.cellml.org/

The CellML language is an open standard based on the XML markup language. The purpose of CellML is to store and exchange computer-based mathematical models. CellML allows scientists to share models even if they are using different model-building software. It also enables them to reuse components from one model in another, thus accelerating model building. Although CellML was originally intended for the description of biological models; CellML includes information about model structure (how the parts of a model are organizationally related to one another), mathematics (equations describing the underlying processes) and metadata (additional information about the model that allows scientists to search for specific models or model components in a database or other repository). The CellML team is committed to providing freely available tools for creating, editing, and using CellML models. We provide information regarding tools we are developing internally and links to external projects developing tools which utilize the CellML format. Please let us know if you have an open source CellML tool looking for a home on the internet, as we are able to offer limited hosting services on cellml.org.

Proper citation: CellML (RRID:SCR_008061) Copy   

•   Source: SciCrunch Registry

http://www.orcid.org/

Non-profit organization dedicated to solving the author/contributor name ambiguity problem in scholarly communications by creating a central registry of unique identifiers for individual researchers and an open and transparent linking mechanism between ORCID and other current author ID schemes. These identifiers, and the relationships among them, can be linked to the researcher''s output to enhance the scientific discovery process and to improve the efficiency of research funding and collaboration within the research community. The ideal solution is to establish a registry that is adopted and embraced as the de facto standard by the whole of the community. A resolution to the systemic name ambiguity problem, by means of assigning unique identifiers linkable to an individual''s research output, will enhance the scientific discovery process and improve the efficiency of funding and collaboration. The organization brings together the leaders of the most influential universities, funding organizations, societies, publishers and corporations from around the globe and is managed by a fourteen member Board of Directors. A disambiguated set of authors will allow new services and benefits to be built for the research community by all stakeholders in scholarly communication: from commercial actors to non-profit organizations, from governments to universities.

Proper citation: ORCID - Open Researcher and Contributor ID (RRID:SCR_008700) Copy   

•   Source: SciCrunch Registry

https://github.com/xavierdidelot/clonalorigin

Software package for comparative analysis of the sequences of a sample of bacterial genomes in order to reconstruct the recombination events that have taken place in their ancestry.

Proper citation: ClonalOrigin (RRID:SCR_016061) Copy   

•   Source: SciCrunch Registry

https://sanger-pathogens.github.io/Roary/

Software tool for rapid large scale prokaryote pan genome analysis. Builds large scale pan genomes, identifying core and accessory genes. Makes construction of pan genome of thousands of prokaryote samples on standard desktop without compromising on accuracy of results. Not intended for meta genomics or for comparing extremely diverse sets of genomes.

Proper citation: Roary (RRID:SCR_018172) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

https://www.gencodegenes.org

Human and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.

Proper citation: GENCODE (RRID:SCR_014966) Copy   

•   Source: SciCrunch Registry

http://www.evocontology.org/site/Main/EvocOntologyDotOrg

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented September 6, 2016. Set of orthogonal controlled vocabularies that unifies gene expression data by facilitating a link between the genome sequence and expression phenotype information. The system associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. The four core eVOC ontologies provide an appropriate set of detailed human terms that describe the sample source of human experimental material such as cDNA and SAGE libraries. These expression terms are linked to libraries and transcripts allowing the assessment of tissue expression profiles, differential gene expression levels and the physical distribution of expression across the genome. Analysis is currently possible using EST and SAGE data, with microarray data being incorporated. The eVOC data is increasingly being accepted as a standard for describing gene expression and eVOC ontologies are integrated with the Ensembl EnsMart database, the Alternate Transcript Diversity Project and the UniProt Knowledgebase. Several groups are currently working to provide shared development of this resource such that it is of maximum use in unifying transcript expression information.

Proper citation: eVOC (RRID:SCR_010704) Copy   

•   Source: SciCrunch Registry