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http://www.mrc-cbu.cam.ac.uk/Imaging

Portal where neuroimaging studies are carried out using a Siemens 3T Tim Trio Magnetic Resonance Imaging (or MRI) scanner that is wholly dedicated to studies in Cognitive Neuroscience. From emotions and memories to language and learning, functional neuroimaging is being applied in many different areas of Cognitive Neuroscience. In many cases, this research relies upon support from healthy volunteers although neuroimaging studies are also being conducted in various clinical populations, including depression, anxiety, Parkinson's disease and Alzheimer's disease.

Proper citation: CBU Imaging Wiki (RRID:SCR_003014) Copy   

•   Source: SciCrunch Registry

http://www.nigms.nih.gov/Research/

NIGMS places great emphasis on the support of individual, investigator-initiated grants within its scientific mission areas. Most grants are for research projects (R01), but NIGMS also funds program projects (P01) as well as some research resources. The Institute encourages research in certain scientific areas through requests for applications and program announcements. This website has information for upcoming grants, minority grants as well as training opportunities in medical research in the following disciplines: cell biology, biophysics, genetics, developmental biology, pharmacology, physiology, biological chemistry, bioinformatics, and computational biology.

Proper citation: National Institute of General Medical Sciences: Research Funding (RRID:SCR_003096) Copy   

•   Source: SciCrunch Registry

http://adni-info.org/

Database of the results of the ADNI study. ADNI is an initiative to develop biomarker-based methods to detect and track the progression of Alzheimer's disease (AD) that provides access to qualified scientists to their database of imaging, clinical, genomic, and biomarker data.

Proper citation: ADNI - Alzheimer's Disease Neuroimaging Initiative (RRID:SCR_003007) Copy   

•   Source: SciCrunch Registry

http://bioinfo.cipf.es/noiseq/doku.php?id=start

Software used for the identification of differentially expressed genes from count data or previously normalized count data. It empirically models the noise distribution of count changes by contrasting fold-change differences (M) and absolute expression differences (D) for all the features in samples within the same condition. This reference distribution is then used to assess whether the M-D values computed between two conditions for a given gene is likely to be part of the noise or represent a true differential expression.

Proper citation: NOISeq (RRID:SCR_003002) Copy   

•   Source: SciCrunch Registry

http://www.cambridgecognition.com/

Global commercial provider of cognitive assessment software for clinical trials, academic research and healthcare provision.

Proper citation: Cambridge Cognition (RRID:SCR_003001) Copy   

•   Source: SciCrunch Registry

http://genome.ucsc.edu/cgi-bin/hgPcr?command=start

Tool that searches a sequence database with a pair of PCR primers, using an indexing strategy for fast performance. When successful, the search returns a sequence output file in fasta format containing all sequence in the database that lie between and include the primer pair. The fasta header describes the region in the database and the primers. The fasta body is capitalized in areas where the primer sequence matches the database sequence and in lower-case elsewhere. Sources and executables to run batch jobs on your own server are available free for academic, personal, and non-profit purposes. Non-exclusive commercial licenses are also available.

Proper citation: In-Silico PCR (RRID:SCR_003089) Copy   

•   Source: SciCrunch Registry

http://celeganskoconsortium.omrf.org

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The mission of the C. elegans Gene Knockout Consortium is to facilitate genetic research of this important model system through the production of deletion alleles at specified gene targets. We choose targets based on investigator requests. Strains produced by the consortium are freely available with no restrictions to any investigator. At one time, our capacity dictated that we restrict requests to five per lab. This restriction no longer holds. Investigators are encouraged especially to register requests for functionally related groups of genes. Consortium strains are distributed by the C. elegans Genetic Center (CGC). In most cases, when you use the Consortium web site to request an existing allele, your request is forwarded automatically to the CGC. However, if you indicate that an existing allele is not satisfactory for your research, (for whatever reason), you may request that we generate another allele for the same target. Any information generated by the Consortium is entered into the official C. elegans data repository, WormBase.

Proper citation: C. elegans Gene Knockout Consortium (RRID:SCR_003000) Copy   

•   Source: SciCrunch Registry

http://www.biomarkersconsortium.org/

Consortium serving to develop and qualify promising biomarkers in order to help accelerate the delivery of successful new technologies, medicines and therapies for prevention, early detection, diagnosis and treatment of disease. Current core disease areas of focus include Cancer, Inflammation and Immunity, Metabolic Disorders, and Neuroscience. One of the most difficult tasks facing biomarker assessment and evaluation is harmonizing the approaches of various stakeholders--government, industry, non-profits and foundations, providers, and academic institutions. Consortium founding members and other partners recognize the critical need for a coordinated cross-sector partnership effort. The Biomarkers Consortium brings together the expertise and resources of various partners to rapidly identify, develop, and qualify potential high-impact biomarkers. Biomarkers Consortium Goals: * Facilitate the development and qualification of biomarkers using new and existing technologies; * Help qualify biomarkers for specific applications in diagnosing disease, predicting therapeutic response or improving clinical practice; * Generate information useful to inform regulatory decision making; * Make consortium project results broadly available to the entire scientific community.

Proper citation: Biomarkers Consortium (RRID:SCR_003121) Copy   

•   Source: SciCrunch Registry

http://empress.har.mrc.ac.uk

Database of validated Standard Operating Procedures (SOPs) for screens to determine the phenotype of a mouse, developed by the EUMORPHIA consortium. The SOP's cover all of the main body systems including: clinical chemistry, hormonal and metabolic systems, cardiovascular, allergy and infection, renal function, sensory function, neurological and behavioral function, cancer, bone and cartilage, and respiratory function. In addition, there are generic SOPs in histology, necropsy, pathology and gene expression. EMPReSS is a platform of individual tests. These can be performed as individual tests or grouped together in sequences, recommended in the EMPReSS database, to give more information on particular phenotype. Quick List of Current Pipelines: * EUMODIC Pipeline 1 * EUMODIC Pipeline 2 * GMC Pipeline * MGP Pipeline * Additional Tests * EUMODIC Pipeline 3

Proper citation: European Mouse Phenotyping Resource of Standardised Screens (RRID:SCR_003087) Copy   

•   Source: SciCrunch Registry

http://elm.eu.org

Computational biology resource for investigating candidate functional sites in eukarytic proteins. Functional sites which fit to the description linear motif are currently specified as patterns using Regular Expression rules. To improve the predictive power, context-based rules and logical filters are being developed and applied to reduce the amount of false positives. The current version of the ELM server provides core functionality including filtering by cell compartment, phylogeny, globular domain clash (using the SMART/Pfam databases) and structure. In addition, both the known ELM instances and any positionally conserved matches in sequences similar to ELM instance sequences are identified and displayed (see ELM instance mapper). Although the ELM resource contains a large collection of functional site motifs, the current set of motifs is not exhaustive.

Proper citation: Eukaryotic Linear Motif (RRID:SCR_003085) Copy   

•   Source: SciCrunch Registry

https://github.com/biojs

An open source JavaScript library of components for visualisation of biological data on the web.

Proper citation: BioJS (RRID:SCR_003119) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/SPD

An ontology for spider comparative biology including anatomical parts (e.g. leg, claw), behavior (e.g. courtship, combing) and products (i.g. silk, web, borrow).

Proper citation: Spider Ontology (RRID:SCR_003117) Copy   

•   Source: SciCrunch Registry

https://github.com/CRG-Barcelona/bwtool/wiki

A command-line utility for bigWig files designed to read bigWig files rapidly and efficiently, providing functionality for extracting data and summarizing it in several ways, globally or at specific regions. Its functionality is subdivided into subprograms that roughly fall into three categories: data extraction, analysis, and data modification, although e.g. in the case of the matrix program or the sax program, the boundary between data extraction and analysis isn't very strong. The data modification programs all have the behavior that a bigWig is inputted and a new bigWig is outputted.

Proper citation: bwtool (RRID:SCR_003035) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/enviPat/

Software for fast and very memory-efficient calculation of isotope patterns, subsequent convolution to theoretical envelopes (profiles) plus valley detection and centroidization or intensoid calculation. Batch processing, resolution interpolation, wrapper, adduct calculations and molecular formula parsing.

Proper citation: enviPat (RRID:SCR_003034) Copy   

•   Source: SciCrunch Registry

http://cytoscape.org

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

Proper citation: Cytoscape (RRID:SCR_003032) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/mosdi/

Sequence analysis toolkit that contains a lot of sequence analysis algorithms, including methods for 1) motif statistics, e.g. compute the exact occurrence count distribution of a motif, 2) exact motif discovery: extraction of motifs with provably optimal p-value, 3) analysis of pattern matching algorithms: compute (for given algorithm and pattern) the exact distribution of the number of character accesses caused by searching a random text, 4) statistics of fragment masses resulting from proteolytic cleavage of proteins, 5) computing the expectated read length of sequencing reads for a given dispensation order (for 454 or IonTorrent) and 6) analysing sensitivity of spaced alignment seeds.

Proper citation: MoSDi (RRID:SCR_003037) Copy   

•   Source: SciCrunch Registry

http://www.diabetesgenome.org

Produce resources to unravel the interface between insulin action, insulin resistance and the genetics of type 2 diabetes including an annotated public database, standardized protocols for gene expression and proteomic analysis, and ultimately diabetes-specific and insulin action-specific DNA chips for investigators in the field. The project aims to identify the sets of the genes involved in insulin action and the predisposition to type 2 diabetes, as well as the secondary changes in gene expression that occur in response to the metabolic abnormalities present in diabetes. There are five major and one pilot project involving human and rodent tissues that are designed to: * Create a database of the genes expressed in insulin-responsive tissues, as well as accessible tissues, that are regulated by insulin, insulin resistance and diabetes. * Assess levels and patterns of gene expression in each tissue before and after insulin stimulation in normal and genetically-modified rodents; normal, insulin resistant and diabetic humans, and in cultured and freshly isolated cell models. * Correlate the level and patterns of expression at the mRNA and/or protein level with the genetic and metabolic phenotype of the animal or cell. * Generate genomic sequence from a panel of humans with type 2 diabetes focusing on the genes most highly regulated by insulin and diabetes to determine the range of sequence and expression variation in these genes and the proteins they encode, which might affect the risk of diabetes or insulin resistance. The DGAP project will define: * the normal anatomy of gene expression, i.e. basal levels of expression and response to insulin. * the morbid anatomy of gene expression, i.e., the impact of diabetes on expression patterns and the insulin response. * the extent to which genetic variability might contribute to the alterations in expression or to diabetes itself.

Proper citation: DGAP (RRID:SCR_003036) Copy   

•   Source: SciCrunch Registry

http://jaspar.genereg.net

Open source database of curated, non-redundant set of profiles derived from published collections of experimentally defined transcription factor binding sites for multicellular eukaryotes. Consists of open data access, non-redundancy and quality. JASPAR CORE is smaller set that is non-redundant and curated. Collection of transcription factor DNA-binding preferences, modeled as matrices. These can be converted into Position Weight Matrices (PWMs or PSSMs), used for scanning genomic sequences. Web interface for browsing, searching and subset selection, online sequence analysis utility and suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval.

Proper citation: JASPAR (RRID:SCR_003030) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/gel2de/

Software application for performing pixel-by-pixel correlation analysis on a set of gel images from two-dimensional gel electrophoresis and a set of clinical parameters for a population. The application is written in C++, and has been tested on Windows, although it in principle should compile cross platform using CMake.

Proper citation: Gel2DE (RRID:SCR_002977) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics.babraham.ac.uk/projects/chipmonk/

Software tool to visualize and analyse ChIP-on-chip array data. Main features: * Import of data from Nimblegen arrays (other formats can be added if people send us examples) * Normalization of data (both per array and per probe) * Various data plotting options to assess data quality and the effectiveness of normalization * Creation of data groups for visualization and analysis * Visualization of data against an annotated genome. * Statistical analysis of data to find probes of interest * Creation of reports containing probes, data and genome annotation Note: This project is no longer being developed, but critical bug fixes will still be provided

Proper citation: ChIPMonk (RRID:SCR_002975) Copy   

•   Source: SciCrunch Registry