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http://www.lhasalimited.org/

A not-for-profit membership organization and educational charity that facilitates collaborative data sharing projects in the pharmaceutical, cosmetics and chemistry-related industries specializing in the development of expert computer systems for toxicity and metabolism prediction. They provide a number of extensive and continually updated knowledge bases and the software needed to interrogate them. Its charitable aims include the sponsorship of activities that advance scientific knowledge and understanding and they regularly support computational chemistry events and initiatives that are of interest to Lhasa Limited members and the wider scientific community. All applications for sponsorship will be considered on their individual merits.

Proper citation: Lhasa Limited (RRID:SCR_003775) Copy   

•   Source: SciCrunch Registry

http://www.oncotrack.eu/

An international consortium to develop and assess novel approaches to identify and characterize biological markers for colon cancer that will deepen the understanding of the variable make-up of tumors and how this affects the way patients respond to treatment. They will use cutting edge laboratory-based genome sequencing techniques coupled to novel computer modelling approaches to study both the biological heterogeneity of colon cancers (i.e. patient to patient variability) as well as tumor variation within the patient for example, by comparing primary tumors with metastases. This five year project brings together top scientists from European academic institutions offering a wide range of expertise, and partners them with pharmaceutical companies. The project is based on the premise that this genetic and epigenetic information, combined with a description of the molecular pathology of the tumor, will allow OncoTrack to generate a more accurate in-silico model of the cancer cell. This will facilitate the identification of predictive markers that can be used to guide the optimal therapy strategy at the level of the individual patient - and will also provide on-going prognostic guidance for the clinician. This project will not only advance understanding of the fundamental biology of colon cancers but will provide the means and approach for the identification of previously undetected biomarkers not only in the cancer under study, but potentially also in other solid cancers and, in doing so, open the door for personalized management of the oncology patient.

Proper citation: OncoTrack (RRID:SCR_003767) Copy   

•   Source: SciCrunch Registry

http://www.predict-tb.eu/

Consortium to accelerate the search for new, more effective combinations of treatments to tackle Tuberculosis and address pre-clinical research barriers to the discovery and development of new TB drug combinations. To overcome the challenges in Tuberculosis drug development they will create tools to accelerate PK-PD (Pharmacokinetic / Pharmacodynamic) analysis that are connected to clinical outcomes. By addressing the gaps in preclinical information, the consortium aims to provide a framework and tools to facilitate the transition of the best combinations of drugs to late phase development. They aim to develop an integrated set of laboratory-based models that will provide much-needed data to indicate the most appropriate doses and combinations of drugs for patients. In addition, the project will generate a comprehensive database of patient data from previous and on-going clinical trials for use as a reference for evaluating the performance of combination anti-TB drug regimens in these newly developed laboratory models. Ultimately, they aim to enable researchers to be able to use the information generated by the novel models to design better clinical trials involving TB patients. The aims of the consortium: * To systematically evaluate two successive panels of representative anti-tuberculosis drugs (licensed and novel) using a suite of standard, novel and enhanced preclinical model systems, with respect to performance in clinical trials * To refine the set of preclinical systems on the basis of these results in order to identify and define the currently optimal critical path in discovery and pre-clinical development for tuberculosis. * To develop an integrated PK-PD / Disease modelling and simulation framework for tuberculosis which will facilitate prediction of optimal combinations and design of clinical studies.

Proper citation: Predict-TB (RRID:SCR_003766) Copy   

•   Source: SciCrunch Registry

http://www.ucsd.tv/stein/

Videos and podcasts presenting the latest innovative research being conducted by the Stein Institute for Research on Aging medical faculty, with the aim of promoting healthy aging. Additionally, many of the public lectures from the Public Lecture Series are also available on UCSD-TV's website video on demand programming. The Lecture series allows affiliated faculty members of the Stein Institute for Research on Aging and other scientists from the UCSD School of Medicine, as well as individuals from surrounding academic and research institutions, to present the latest findings in their respective fields of expertise and share their present work with the general community. All of these lectures focus on topics related to healthy aging or age-related diseases.

Proper citation: Stein Institute for Research on Aging Video Archive (RRID:SCR_003761) Copy   

•   Source: SciCrunch Registry

http://www.etriks.org/

Research informatics and analytics platform for the IMI OncoTrack consortium.

Proper citation: eTRIKS (RRID:SCR_003765) Copy   

•   Source: SciCrunch Registry

http://www.psidev.info/index.php?q=node/257

Markup language for encoding raw spectrometer output. From 2005-2008 there has existed two separate XML formats for encoding raw spectrometer output: mzData developed by the PSI and mzXML developed at the Seattle Proteome Center at the Institute for Systems Biology. It was recognized that the existence of two separate formats for essentially the same thing generated confusion and required extra programming effort. Therefore the PSI, with full participation by ISB, has developed a new format by taking the best aspects of each of the precursor formats to form a single one. It is intended to replace the previous two formats. This new format was originally given a working name of dataXML. The final name is mzML.

Proper citation: mzML (RRID:SCR_003763) Copy   

•   Source: SciCrunch Registry

http://www.tipharma.com/

A not-for-profit organization that initiates and manages drug development consortia that involve the pharmaceutical industry, academia, and the Dutch Government. The aim of all their consortia is to conduct pre-competitive research while strengthening the Netherlands' international reputation for drug development. The consortia are focused on addressing therapeutic areas that are listed as priority areas by the World Health Organization including: autoimmune diseases, cardiovascular diseases, cancer, infectious diseases, and diseases of the brain. The consortia are also focused on enabling: therapeutic target discovery, validation, and animal models; lead selection and in-silico modeling; predictive drug disposition and toxicology; biomarkers and biosensors; drug formulation, delivery, and targeting; and, production technologies. TI Pharma consortia aim to improve the efficiency of the drug-development process, with a focus on advancing regulatory science. In addition to research, TI Pharma also has objectives to train and educate scientists in the Netherlands on the drug discovery and development processes, as well as on entrepreneurship. Participants include: all Dutch universities and academic medical centers, more than 30 industrial partners, small-to-medium sized companies, and representatives from the Dutch Medicines Evaluation Board (Netherlands regulatory body for drugs).

Proper citation: TI Pharma (RRID:SCR_003758) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.bc.edu/marthlab/wiki/index.php/PyroBayes

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. A base caller for pyrosequences from the 454 Life Sciences sequencing machines.

Proper citation: PyroBayes (RRID:SCR_003757) Copy   

•   Source: SciCrunch Registry

https://www.nanoporetech.com/

Commercial organization developing a disruptive, proprietary technology platform for the direct, electronic analysis of single molecules. The instruments GridION and MinION are adaptable for the analysis of DNA, RNA, proteins, small molecules and other types of molecule. Consequently, the platform has a broad range of potential applications, including scientific research, personalized medicine, crop science and security / defence.

Proper citation: Oxford Nanopore Technologies (RRID:SCR_003756) Copy   

•   Source: SciCrunch Registry

http://neuroscienceblueprint.nih.gov/

Collaborative framework that includes the NIH Office of the Director and the 14 NIH Institutes and Centers that support research on the nervous system. By pooling resources and expertise, the Blueprint identifies cross-cutting areas of research, and confronts challenges too large for any single Institute or Center. The Blueprint makes collaboration a day-to-day part of how the NIH does business in neuroscience, complementing the basic missions of Blueprint partners. During each fiscal year, the partners contribute a small percentage of their funds to a common pool. Since the Blueprint's inception in 2004, this pool has comprised less than 1 percent of the total neuroscience research budget of the partners. In 2009, the Blueprint Grand Challenges were launched to catalyze research with the potential to transform our basic understanding of the brain and our approaches to treating brain disorders. * The Human Connectome Project is an effort to map the connections within the healthy brain. It is expected to help answer questions about how genes influence brain connectivity, and how this in turn relates to mood, personality and behavior. The investigators will collect brain imaging data, plus genetic and behavioral data from 1,200 adults. They are working to optimize brain imaging techniques to see the brain's wiring in unprecedented detail. * The Grand Challenge on Pain supports research to understand the changes in the nervous system that cause acute, temporary pain to become chronic. The initiative is supporting multi-investigator projects to partner researchers in the pain field with researchers in the neuroplasticity field. * The Blueprint Neurotherapeutics Network is helping small labs develop new drugs for nervous system disorders. The Network provides research funding, plus access to millions of dollars worth of services and expertise to assist in every step of the drug development process, from laboratory studies to preparation for clinical trials. Project teams across the U.S. have received funding to pursue drugs for conditions from vision loss to neurodegenerative disease to depression. Since its inception in 2004, the Blueprint has supported the development of new resources, tools and opportunities for neuroscientists. For example, the Blueprint supports several training programs to help students pursue interdisciplinary areas of neuroscience, and to bring students from underrepresented groups into the neurosciences. The Blueprint also funds efforts to develop new approaches to teaching neuroscience through K-12 instruction, museum exhibits and web-based platforms. From fiscal years 2007 to 2009, the Blueprint focused on three major themes of neuroscience - neurodegeneration, neurodevelopment, and neuroplasticity. These efforts enabled unique funding opportunities and training programs, and helped establish new resources including the Blueprint Non-Human Primate Brain Atlas.

Proper citation: NIH Blueprint for Neuroscience Research (RRID:SCR_003670) Copy   

•   Source: SciCrunch Registry

http://www.addconsortium.org/

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   

•   Source: SciCrunch Registry

http://www.ebioscience.com/

An Antibody supplier

Proper citation: eBioscience (RRID:SCR_003660) Copy   

•   Source: SciCrunch Registry

http://www.sabbiotech.com/

An Antibody supplier

Proper citation: Signalway (RRID:SCR_003659) Copy   

•   Source: SciCrunch Registry

http://www.evoio.org/wiki/MIAPA

Central hub for resources related to developing and deploying a Minimal Information for a Phylogenetic Analysis (MIAPA) standard.

Proper citation: MIAPA (RRID:SCR_003777) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/efo/

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   

•   Source: SciCrunch Registry

http://genome.sph.umich.edu/wiki/RAREMETAL

A software program that facilitates the meta-analysis of rare variants from genotype arrays or sequencing.

Proper citation: RAREMETAL (RRID:SCR_003573) Copy   

•   Source: SciCrunch Registry

http://www.isi.edu/integration/karma/

An information integration software tool that enables users to integrate data from a variety of data sources including databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs. Users integrate information by modeling it according to an ontology of their choice using a graphical user interface that automates much of the process. Karma learns to recognize the mapping of data to ontology classes and then uses the ontology to propose a model that ties together these classes. Users then interact with the system to adjust the automatically generated model. During this process, users can transform the data as needed to normalize data expressed in different formats and to restructure it. Once the model is complete, users can publish the integrated data as RDF or store it in a database.

Proper citation: Karma (RRID:SCR_003732) Copy   

•   Source: SciCrunch Registry

http://www.asf.alaska.edu/

Satellite facility that downlinks, processes, archives, and distributes remote-sensing data to scientific users around the world. Three major components: * Satellite Tracking Ground Station: Part of NASA?s Near Earth Network system of ground stations around the world. * Synthetic Aperture Radar Distributed Active Archive Center (SAR DAAC): ASF maintains the NASA archive of SAR data from a variety of satellites and aircraft, and provides these data and associated specialty support services to U.S. Government-approved researchers in support of NASA?s Earth Science Data and Information System project. * ASF Enterprise Center (ASFE): In support of UAF?s mission to be a student-centered research university, the ASF-E focuses on applications of remote-sensing data, specifically for UAF research. The ASF-E includes the GeoData Center (GDC), which provides data management and archive services for UAF principal investigators and maintains a variety of geophysical data collections in support of scientific research.

Proper citation: Alaska Satellite Facility (RRID:SCR_003610) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.myelinrepair.org/

A non-profit foundation that funds basic research and is focused on accelerating the development of myelin repair therapeutics for multiple sclerosis. They have defined a 15-year research plan to develop a drug or drugs and believes its Accelerated Research Collaborative (ARC) model can subsequently be used to accelerate the treatment for all diseases. The ARC framework coordinates and manages the entire therapeutic development continuum from discovery biology to FDA approval. The model works by coordinating multi-disciplinary basic research from academic and government laboratories, systematically validating and derisking potential compounds/targets, and collaborating with pharma partners to increase the probability of successful programs.

Proper citation: Myelin Repair Foundation (RRID:SCR_003723) Copy   

•   Source: SciCrunch Registry