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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Evidence based, expert curated knowledge base for synapse. Universal reference for synapse research and online analysis platform for interpretation of omics data. Interactive knowledge base that accumulates available research about synapse biology using Gene Ontology annotations to novel ontology terms.
Proper citation: SynGO (RRID:SCR_017330) Copy
EU data infrastructure with workflow connectivity layer. Common Workflow Language. Project pioneers methodologies and integrated set of supporting technologies that will transform European RIs productivity and rate of innovation when three challenges – extreme data, extreme computation and extreme complexity – are faced simultaneously.
Proper citation: Project DARE (RRID:SCR_017538) Copy
http://bioinformatics.biol.rug.nl/standalone/fiva/
Functional Information Viewer and Analyzer (FIVA) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software is able to assist in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes. Currently, seven different modules containing functional information have been implemented: (i) gene regulatory interactions, (ii) cluster of orthologous groups (COG) of proteins, (iii) gene ontologies (GO), (iv) metabolic pathways (v) Swiss Prot keywords, (vi) InterPro domains - and (vii) generic functional categories. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: FIVA - Functional Information Viewer and Analyzer (RRID:SCR_005776) Copy
European website providing information about orphan drugs and rare diseases. It contains content both for physicians and for patients. Reference portal for rare diseases and orphan drugs to help improve diagnosis, care and treatment of patients with rare diseases.
Proper citation: Orphanet (RRID:SCR_006628) Copy
BBMRI is a pan-European and internationally broadly accessible research infrastructure and a network of existing and de novo biobanks and biomolecular resources. The infrastructure will include samples from patients and healthy persons, representing different European populations (with links to epidemiological and health care information), molecular genomic resources and biocomputational tools to optimally exploit this resource for global biomedical research. During the past 3 years BBMRI has grown into a 53-member consortium with over 280 associated organizations (largely biobanks) from over 30 countries, making it the largest research infrastructure project in Europe. During the preparatory phase the concept of a functional pan-European biobank was formulated and has now been presented to Member States of the European Union and for associated states for approval and funding. BBMRI will form an interface between specimens and data (from patients and European populations) and top-level biological and medical research. This can only be achieved through a distributed research infrastructure with operational units in all participating Member States. BBMRI will be implemented under the ERIC (European Research Infrastructure Consortium) legal entity. BBMRI-ERIC foresees headquarters (central coordination) in Graz, Austria, responsible for coordination of the activities of National Nodes established in participating countries. BBMRI is in the process of submitting its application to the European Commission for a legal status under the ERIC regulation, with an expected start date at the end of 2011. Major synergism, gain of statistical power and economy of scale will be achieved by interlinking, standardizing and harmonizing - sometimes even just cross-referencing - a large variety of well-qualified, up-to date, existing and de novo national resources. The network should cover (1) major European biobanks with blood, serum, tissue or other biological samples, (2) molecular methods resource centers for human and model organisms of biomedical relevance, (3) and biocomputing centers to ensure that databases of samples in the repositories are dynamically linked to existing databases and to scientific literature as well as to statistical expertise. Catalog of European Biobanks www.bbmriportal.eu Username: guest / Password: catalogue The catalogue is intended to be used as a reference for scientists seeking information about biological samples and data suitable for their research. The BBMRI catalogue of European Biobanks provides a high-level description of Europe''s biobanks characteristics using a portal solution managing metadata and aggregate data of biobanks. The catalogue can be queried by country, by biobank, by ICD-groups, by specimen types, by specific strengths, by funding and more. A search function is available for all data.
Proper citation: Biobanking and Biomolecular Resources Research Infrastructure (BBMRI) (RRID:SCR_004226) Copy
http://www.sanger.ac.uk/mouseportal/
Database of mouse research resources at Sanger: BACs, targeting vectors, targeted ES cells, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen. The Wellcome Trust Sanger Institute generates, characterizes, and uses a variety of reagents for mouse genetics research. It also aims to facilitate the distribution of these resources to the external scientific community. Here, you will find unified access to the different resources available from the Institute or its collaborators. The resources include: 129S7 and C57BL6/J bacterial artificial chromosomes (BACs), MICER gene targeting vectors, knock-out first conditional-ready gene targeting vectors, embryonic stem (ES) cells with gene targeted mutations or with retroviral gene trap insertions, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen.
Proper citation: Sanger Mouse Resources Portal (RRID:SCR_006239) Copy
http://www.genomeutwin.org/index.htm
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Study of genetic and life-style risk factors associated with common diseases based on analysis of European twins. The population cohorts used in the Genomeutwin study consist of Danish, Finnish, Italian, Dutch, English, Australian and Swedish twins and the MORGAM population cohort. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterize the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide. The participating 8 twin cohorts form a collection of over 0.6 million pairs of twins. Tens of thousands of DNA samples with informed consents for genetic studies of common diseases have already been stored from these population-based twin cohorts. Studies targeted to cardiovascular traits are now being undertaken in MORGAM, a prospective case-cohort study. MORGAM cohorts include approximately 6000 individuals, drawn from population-based cohorts consisting of more than 80 000 participants who have donated DNA samples.
Proper citation: GenomEUtwin (RRID:SCR_002843) Copy
A research portal to share and obtain research data and journal articles openly accessible to all disciplines. Established to support the Open Access Policy, as set out by the ERC Scientific Council Guidelines for Open Access and the Open Access pilot launched by the European Commission.
Proper citation: OpenAIRE (RRID:SCR_013740) Copy
https://www.sanger.ac.uk/science/tools/reapr
Software tool to identify errors in genome assemblies without need for reference sequence. Can be used in any stage of assembly pipeline to automatically break incorrect scaffolds and flag other errors in assembly for manual inspection. Reports mis-assemblies and other warnings, and produces new broken assembly based on error calls.
Proper citation: Recognition of Errors in Assemblies using Paired Reads (RRID:SCR_017625) Copy
https://juaml.github.io/julearn
Software library of easy testing ML models directly from pandas DataFrames, while keeping the flexibility of using scikit-learn’s models.
Proper citation: Julearn (RRID:SCR_024881) Copy
Web interactive browser to visualize data and perform gene set enrichment analysis along with gene and SNP lookup. Web interface used to query STARNET datasets and downstream analysis which includes RNAseq from 7 tissues: blood, free internal mammary artery (MAM), atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV). Paired SNP genotyping data is included and utilized for tissue expression quantitative trait loci (eQTL), CAD heritability (H2), co-expression networks and gene regulatory networks.
Proper citation: STARNET (RRID:SCR_025238) Copy
Portal provides information about available datasets, resources, tools, and services related to pandemic preparedness in Norway. Portal gives researchers, clinicians and policymakers access to collection of biomolecular data about pathogens.
Proper citation: Pathogens Portal Norway (RRID:SCR_025641) Copy
Software tool for description of connectivity in small and large scale neuronal network models. It provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. Can be used as component of neuronal network simulators or other tools.
Proper citation: Connection-set algebra (RRID:SCR_017397) Copy
http://www.alzheimer-europe.org/
A non-governmental organization aimed at raising awareness of all forms of dementia by creating a common European platform through co-ordination and co-operation between Alzheimer organizations throughout Europe. Alzheimer Europe is also a source of information on all aspects of dementia.
Proper citation: Alzheimer Europe (RRID:SCR_003802) Copy
https://github.com/farkkilab/tribus
Software tool for cell type based analysis of multiplexed imaging data. Interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. Recovers fine-grained cell types, matching the gold standard annotations by human experts, can target ambiguous populations and discover phenotypically distinct cell subtypes.
Proper citation: TRIBUS (RRID:SCR_027367) Copy
http://www.brenda-enzymes.org/
Database for functional enzyme and ligand-related information maintained as part of the German ELIXIR Node. Provides advanced query systems, evaluation tools, and various visualization options for the detailed assessment of enzyme properties. Enzyme data in BRENDA are classified according to the Enzyme Commission (EC) nomenclature of IUBMB.
Proper citation: BRENDA (RRID:SCR_002997) Copy
A software application which assists in managing and sharing scientific literature. Users can collect and share publications, collaborate with other researchers, and find new resources and publications for research.
Proper citation: BibSonomy (RRID:SCR_013756) Copy
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
http://cordis.europa.eu/project/rcn/98370_en.html
The Colon Therapy Research (COLTHERES) consortium brings together clinical centers and translational researchers funded in the European Union to define and perform biomarker driven clinical trials to improve cancer therapy outcomes. This 4-year consortium will use comprehensively molecularly-annotated colon cancers as a "test-bed" to define specific biomarkers of response or resistance to signaling pathway agents.
Proper citation: Colon Therapy Research Consortium (COLTHERES) (RRID:SCR_013690) Copy
https://github.com/ledancs/hFigures
A Javascript library that aims to deliver a starting point for interactive health data visualization. Examples and demos are available on the site. hFigures was built with d3.js and a copy of the library is included in this repository. All rights and license terms apply to the d3.js library accordingly.
Proper citation: hFigures (RRID:SCR_014201) Copy
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