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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.
A collaborative network among university-led drug discovery centers and programs to allow scientists to exchange technical expertise on drug discovery and development strategies as well as form partnerships with each other, biopharma companies, and drug discovery-focused contract service organizations and consultants. The website will also serve as a repository for drug discovery events, educational material, job postings, and partnership opportunities. Through active member participation this website will become a valuable tool for every scientist working in the drug discovery arena. In addition, involvement of members will enable them to effectively advocate to the NIH and other funding agencies to increase the awareness of the growing number of academic drug discovery scientists and their success as well as their needs.
Proper citation: Academic Drug Discovery Consortium (RRID:SCR_003706) Copy
http://www.europeanlung.org/en/projects-and-research/projects/airprom/
Consortium focused on developing computer and physical models of the airway system for patients with asthma and chronic obstructive pulmonary disease (COPD). Developing accurate models will better predict how asthma and COPD develop, since current methods can only assess the severity of disease. They aim to bridge the gaps in clinical management of airways-based disease by providing reliable models that predict disease progression and the response to treatment for each person with asthma or COPD. A data management platform provides a secure and sustainable infrastructure that semantically integrates the clinical, physiological, genetic, and experimental data produced with existing biomedical knowledge from allied consortia and public databases. This resource will be available for analysis and modeling, and will facilitate sharing, collaboration and publication within AirPROM and with the broader community. Currently the AirPROM knowledge portal is only accessible by AirPROM partners.
Proper citation: AirPROM (RRID:SCR_003827) Copy
http://www.agedbrainsysbio.eu/
Consortium focused on identifying the foundational pathways responsible for the aging of the brain, with a focus on Late Onset Alzheimer's disease. They aim to identify the interactions through which the aging phenotype develops in normal and in disease conditions; modeling novel pathways and their evolutionary properties to design experiments that identify druggable targets. As early steps of neurodegenerative disorders are expected to impact synapse function the project will focus in particular on pre- or postsynaptic protein networks. The concept is to identify subsets of pathways with two unique druggable hallmarks, the validation of interactions occurring locally in subregions of neurons and a human and/or primate accelerated evolutionary signature. The consortium will do this through six approaches: * identification of interacting protein networks from recent Late-Onset Alzheimer Disease-Genome Wide Association Studies (LOAD-GWAS) data, * experimental validation of interconnected networks working in subregion of a neuron (such as dendrites and dendritic spines), * inclusion of these experimentally validated networks in larger networks obtained from available databases to extend possible protein interactions, * identification of human and/or primate positive selection either in coding or in regulatory gene sequences, * manipulation of these human and/or primate accelerated evolutionary interacting proteins in human neurons derived from induced Pluripotent Stem Cells (iPSCs) * modeling predictions in drosophila and novel mouse transgenic models * validation of new druggable targets and markers as a proof-of-concept towards the prevention and cure of aging cognitive defects. The scientists will share results and know-how on Late-Onset Alzheimer Disease-Genome Wide Association Studies (LOAD-GWAS) gene discovery, comparative functional genomics in mouse and drosophila models, in mouse transgenic approaches, research on human induced pluripotent stem cells (hiPSC) and their differentiation in vitro and modeling pathways with emphasis on comparative and evolutionary aspects. The four European small to medium size enterprises (SMEs) involved will bring their complementary expertise and will ensure translation of project results to clinical application.
Proper citation: AgedBrainSYSBIO (RRID:SCR_003825) Copy
http://graphml.graphdrawing.org/
A file format for graphs that consists of a language core to describe the structural properties of a graph and a flexible extension mechanism to add application-specific data. It is based on XML and is ideally suited as a common denominator for all kinds of services generating, archiving, or processing graphs. Its main features include support of * directed, undirected, and mixed graphs, * hypergraphs, * hierarchical graphs, * graphical representations, * references to external data, * application-specific attribute data, and * light-weight parsers.
Proper citation: GraphML (RRID:SCR_003545) Copy
A consortium of leading biobanks and international researchers from all domains of biobanking science to ensure the development of harmonized measures and standardized computing infrastructures enabling the effective pooling of data and key measures of life-style, social circumstances and environment, as well as critical sub-components of the phenotypes associated with common complex diseases. The overall aim is to build upon tools and methods available to achieve solutions for researchers to use pooled data from different cohort and biobank studies. This, in order to obtain the very large sample sizes needed to investigate current questions in multifactorial diseases, notably on gene-environment interactions. This aim will be achieved through the development of harmonization and standardization tools, implementation of these tools and demonstration of their applicability. BioSHaRE researchers are collaborating with P3G, the Global Alliance for Genomics and Health, IRDiRC (International Rare Diseases Research Consortium), H3Africa and other organizations on the development of an International Code of Conduct for Genomic and Health-Related Data Sharing. A draft version is available for external review. Generic documents have been prepared covering areas of biobanking that are of major importance. SOPs have been finalized for blood withdrawal (SOPWP5001blood withdrawal), manual blood processing (SOPWP5002blood processing), shipping of biosamples (SOPWP5003shipping) and withdrawal, processing and storage of urine samples (SOPWP5004urine).
Proper citation: BioSHaRE (RRID:SCR_003811) Copy
An application focused ontology modelling the experimental factors in ArrayExpress and Gene Expression Atlas. It has been developed to increase the richness of the annotations that are currently made in the ArrayExpress repository, to promote consistent annotation, to facilitate automatic annotation and to integrate external data. The ontology describes cross-product classes from reference ontologies in area such as disease, cell line, cell type and anatomy. The methodology employed in the development of EFO involves construction of mappings to multiple existing domain specific ontologies, such as the Disease Ontology and Cell Type Ontology. This is achieved using a combination of automated and manual curation steps and the use of a phonetic matching algorithm. The ontology is evaluated with use cases from the ArrayExpress repository and ArrayExpress Atlas. You may also browse the EFO in the NCBO Bioportal. Term submissions are welcome.
Proper citation: Experimental Factor Ontology (RRID:SCR_003574) Copy
http://wiki.healthgrid.org/Main_Page
THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. HealthGrid is a wiki dedicated to grids for health. It is maintained as a dynamic knowledge resource for the healthgrid community. The HealthGrid community (a world-wide initiative) gathers individuals from the public and private domain world-wide who are actively exploring the beneficial impact of healthgrid technology on healthcare provision and research.
Proper citation: HealthGrid Wiki (RRID:SCR_003572) Copy
http://code.google.com/p/adverse-event-reporting-ontology/
An ontology aimed at supporting clinicians at the time of data entry, increasing quality and accuracy of reported adverse events.
Proper citation: Adverse Event Reporting Ontology (RRID:SCR_003571) Copy
http://purl.bioontology.org/ontology/MDCDRG
Ontology of Medical Diagnostic Categories-Diagnosis Related Groups
Proper citation: Medical Diagnostic Categories - Diagnosis Related Groups (RRID:SCR_003725) Copy
https://github.com/alyssafrazee/polyester
An R package designed to simulate RNA sequencing experiments with differential transcript expression. Given a set of annotated transcripts, it will simulate the steps of an RNA-seq experiment (fragmentation, reverse-complementing, and sequencing) and produce files containing simulated RNA-seq reads. Simulated reads can be analyzed using a choice of downstream analysis tools. Polyester has a built-in wrapper function to simulate a case/control experiment with differential transcript expression and biological replicates. Users are able to set the levels of differential expression at transcripts of their choosing. This means they know which transcripts are differentially expressed in the simulated dataset, so accuracy of statistical methods for differential expression detection can be analyzed. Polyester offers several unique features: * Built-in functionality to simulate differential expression at the transcript level * Ability to explicitly set differential expression signal strength * Simulation of small datasets, since large RNA-seq datasets can require lots of time and computing resources to analyze * Generation of raw RNA-seq reads, as opposed to alignments or transcript-level abundance estimates * Transparency/open-source code
Proper citation: Polyester (RRID:SCR_003602) Copy
https://www.projectdatasphere.org/
Initiative to advance oncology research by enabling collaborative sharing of historical oncology clinical trial data through a universal platform (database). The initiative aims to network all stakeholders in the cancer community researchers, industry, academia, advocacy, and other organizations to share insights and collaborate on issues that could not be solved individually. To do this, they have made efforts to address issues of data privacy, security, intellectual property, resources, and incentives as part of its effort to maximize participation. Data contributions include control arms of clinical trials, and the platform uses data-security precautions and analytics to pool multiple studies associated with the same diagnosis in a manner that seeks to protect the privacy of patients and the security of the data contributed.
Proper citation: Project Data Sphere (RRID:SCR_003726) Copy
A reference terminology and core biomedical ontology for NCI that covers approximately 100,000 key biomedical concepts with terms, codes, definitions, and more than 200,000 inter-concept relationships. It is the reference terminology for NCI, NCI Metathesaurus and NCI informatics infrastructure covering vocabulary for clinical care, translational and basic research, and public information and administrative activities. It includes broad coverage of the cancer domain, including cancer related diseases, findings and abnormalities; anatomy; agents, drugs and chemicals; genes and gene products and so on. In certain areas, like cancer diseases and combination chemotherapies, it provides the most granular and consistent terminology available. It combines terminology from numerous cancer research related domains, and provides a way to integrate or link these kinds of information together through semantic relationships. NCIt features: * Stable, unique codes for biomedical concepts; * Preferred terms, synonyms, definitions, research codes, external source codes, and other information; * Links to NCI Metathesaurus and other information sources; * Over 200,000 cross-links between concepts, providing formal logic-based definition of many concepts; * Extensive content integrated from NCI and other partners, much available as separate NCIt subsets * Updated frequently by a team of subject matter experts. NCIt is a widely recognized standard for biomedical coding and reference, used by a broad variety of public and private partners both nationally and internationally including the Clinical Data Interchange Standards Consortium Terminology (CDISC), the U.S. Food and Drug Administration (FDA), the Federal Medication Terminologies (FMT), and the National Council for Prescription Drug Programs (NCPDP).
Proper citation: NCI Thesaurus (RRID:SCR_003563) Copy
http://www.themmrf.org/research-programs/commpass-study/
A personalized medicine initiative to discover biomarkers that can better define the biological basis of multiple myeloma to help stratify patients. This effort hopes to obtain samples from approximately 1,000 multiple myeloma patients and follow them over time to identify how a patient's genetic profile is related to clinical progression and treatment response. As a partnership between 17 academic centers, 5 pharmaceuticals and the Department of Veterans Affairs, the goal of this eight year study is to create a database that can accelerate future clinical trials and personalized treatment strategies. MMRF's CoMMpass Study has the following goals: * Create a guide to which treatments work best for specific patient subgroups. * Share data with researchers to accelerate drug development for specific subtypes of multiple myeloma patients. In order to facilitate discoveries and development related to targeted therapies, the comprehensive data from CoMMpass is placed in an open-access research portal. The data will be part of the Multiple Myeloma Research Foundation's (MMRF) Personalized Medicine Platform combines CoMMpass data with those collected from MMRF's Genomics Initiative. It is hoped that the longitudinal data, combined with the annotated bio-specimens will help provide insights that can accelerate personalized therapies.
Proper citation: MMRF CoMMpass Study (RRID:SCR_003721) Copy
EU funded consortium including over 30 partner from academia and industry. BiomarCaRE aims to determine the value of established and emerging biomarkers to improve risk estimation of cardiovascular disease in Europe. BiomarCaRE relies on an exceptional resource of large scale epidemiological cohorts with long term follow-up and available bio specimens based on the population of the MORGAM Project as well as several cardiovascular disease cohorts and clinical trials.
Proper citation: BiomarCaRE (RRID:SCR_003841) Copy
Cure Alzheimer's Fund is a 501(c)(3) public charity. At Cure Alzheimer's Fund, our mission is to fund research with the highest probability of slowing, stopping or reversing Alzheimer's disease. This topical portal has a lot of information including news and blog. Cure Alzheimer's Fund is governed by a board of directors; administered by a small, full-time staff; and guided scientifically by a Research Consortium. A Scientific Advisory Board audits the research program to make sure it is consistent with the objectives of the foundation. Cure Alzheimer's Fund is a doing business as name for the Alzheimer's Disease Research Foundation, federal tax ID # 52-2396428.
Proper citation: Cure Alzheimers Fund (RRID:SCR_003564) Copy
Project that aims to develop new treatment strategies based on knowledge of cellular dysfunction in diabetes. They will perform a detailed organelle diagnosis based on both focused and systems biology approaches, which will provide the scientific rationale for the design of specific interventions to boost the capacity of beta cells and brown adipocytes to regain homeostatic control. They propose that only by understanding the complex molecular mechanisms triggering cellular dysfunction in diabetes, and by integrating this knowledge at the systems level, will it be possible to develop interventional therapies that protect and restore beta cell and (Brown adipose tissue) BAT function. The ultimate goal is to offer individual therapeutic choices based on both genetic information and organelle diagnosis.
Proper citation: BetaBat (RRID:SCR_003834) Copy
Consortium to generate complete catalogs of somatic mutations in 500 breast cancers, of the ER+ve HER2- subclass, under the International Cancer Genome Consortium model by high coverage, shotgun genome sequencing of both tumor and normal DNA. The strategy is to collect, store, review, quality control and extract DNA and RNA from breast cancer and normal tissues from 500 ER+, HER2- breast cancer cases which will be subjected to a coordinated series of genomic analyses including whole genome shotgun sequencing, genome-wide copy number analysis, mRNA expression analysis, miRNA expression analysis and genome-wide methylation analysis. A comprehensive catalogue of somatic mutations will be generated from each cancer. Somatic mutation catalogues from the 500 cancers will be analysed and integrated with expression and methylation data to identify novel cancer genes, characterize subverted biological pathways that are operative, describe patterns of somatic mutation and explore early translational applications of personalized somatic genomic data for patients with ER+, HER2- breast cancer. The results will impact the understanding of the causes and biology of breast cancer and will lead to major advances in detection, prevention and treatment in one of the most common diseases and causes of death in the developed world. The Consortium has completed a number of investigative exercises into the experimental protocols and technological practices relating to whole genome sequencing, epigenetics and transcriptomics including: * Completion of extensive testing of current RNA-seq protocol. * Designed and implemented a new, improved RNA-seq protocol which utilizes RNA samples regardless of their RNA Integrity Number. * Completed pilot testing of the Infinium 450k array and associated bi-sulfite sequencing. * Refined the whole genome sequencing library production protocols to produce more robust libraries. * Improved the primary variant-calling algorithms (for substitutions, insertions / deletions and rearrangements) * Developed new analytical algorithms to explore the resulting high-quality variants. As such, variant calling of whole genome sequencing data and secondary downstream analysis can begin in earnest in a trackable and automated fashion.
Proper citation: Breast Cancer Somatic Genetics Study (RRID:SCR_003832) Copy
http://kongress.mh-hannover.de/biohybrid/
Consortium with the goal of repairing damaged nerve trunks that will engage in the preclinical development of an artificial biohybrid nerve device for the regenerative treatment of traumatic injuries of peripheral nerves. Based on the extensive basic and clinical experience within this consortium the artificial nerve device will be developed together with standardized application and evaluation parameters. A key objective of this study is to generate a protocol that serves as a template for future clinical trials in the regenerative therapy of damaged peripheral nerves. The results of the multidisciplinary research will feed into the establishment of artificial biohybrid devices as stand alone alternatives to accepted standard procedures and tools. Furthermore, standardized application guidelines and evaluation parameters will be set up to enable continuous progress and evaluation of the outcome of clinical application.
Proper citation: BIOHYBRID (RRID:SCR_003838) Copy
Tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. It is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research.
Proper citation: GeneCommittee (RRID:SCR_004168) Copy
Consortium that brings together Europe's top industrial and academic experts to develop new tests that will help researchers detect potential liver toxicity issues much earlier in drug development, saving many patients from the trauma of liver failure. The team aims to deepen the understanding of the science behind drug-induced liver injury, and use that knowledge to overcome the many drawbacks of the tests currently used. A major focus will be on a systematic and evidence-based evaluation of both currently available and new laboratory test systems, including cultures of liver cells in one-dimensional and three dimensional configurations. The project will also develop models that take into account the natural differences between patients. This is important because factors such as certain genes, the liver's immune response, and viral infections have all been associated with an increased risk of DILI. The project will seek to address the current lack of human liver cells available to researchers by using induced pluripotent stem cells (iPSCs) generated from patients who are particularly sensitive to DILI. Another strand of the project will develop computer models to unravel the complex, often inter-related mechanisms behind DILI. Finally, the team will assess how accurate the results of laboratory tests are at predicting actual outcomes in patients.
Proper citation: MIP-DILI (RRID:SCR_003870) Copy
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