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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
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
Research informatics and analytics platform for the IMI OncoTrack consortium.
Proper citation: eTRIKS (RRID:SCR_003765) Copy
http://mimi.ncibi.org/MimiWeb/main-page.jsp
MiMi Web gives you an easy to use interface to a rich NCIBI data repository for conducting your systems biology analyses. This repository includes the MiMI database, PubMed resources updated nightly, and text mined from biomedical research literature. The MiMI database comprehensively includes protein interaction information that has been integrated and merged from diverse protein interaction databases and other biological sources. With MiMI, you get one point of entry for querying, exploring, and analyzing all these data. MiMI provides access to the knowledge and data merged and integrated from numerous protein interactions databases and augments this information from many other biological sources. MiMI merges data from these sources with deep integration into its single database with one point of entry for querying, exploring, and analyzing all these data. MiMI allows you to query all data, whether corroborative or contradictory, and specify which sources to utilize. MiMI displays results of your queries in easy-to-browse interfaces and provides you with workspaces to explore and analyze the results. Among these workspaces is an interactive network of protein-protein interactions displayed in Cytoscape and accessed through MiMI via a MiMI Cytoscape plug-in. MiMI gives you access to more information than you can get from any one protein interaction source such as: * Vetted data on genes, attributes, interactions, literature citations, compounds, and annotated text extracts through natural language processing (NLP) * Linkouts to integrated NCIBI tools to: analyze overrepresented MeSH terms for genes of interest, read additional NLP-mined text passages, and explore interactive graphics of networks of interactions * Linkouts to PubMed and NCIBI's MiSearch interface to PubMed for better relevance rankings * Querying by keywords, genes, lists or interactions * Provenance tracking * Quick views of missing information across databases. Data Sources include: BIND, BioGRID, CCSB at Harvard, cPath, DIP, GO (Gene Ontology), HPRD, IntAct, InterPro, IPI, KEGG, Max Delbreuck Center, MiBLAST, NCBI Gene, Organelle DB, OrthoMCL DB, PFam, ProtoNet, PubMed, PubMed NLP Mining, Reactome, MINT, and Finley Lab. The data integration service is supplied under the conditions of the original data sources and the specific terms of use for MiMI. Access to this website is provided free of charge. The MiMI data is queryable through a web services api. The MiMI data is available in PSI-MITAB Format. These files represent a subset of the data available in MiMI. Only UniProt and RefSeq identifiers are included for each interactor, pathways and metabolomics data is not included, and provenance is not included for each interaction. If you need access to the full MiMI dataset please send an email to mimi-help (at) umich.edu.
Proper citation: Michigan Molecular Interactions (RRID:SCR_003521) Copy
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
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
http://www.cdc.gov/genomics/default.htm
The Office of Public Health Genomics (OPHG) aims to integrate genomics into public health research, policy, and programs. Doing so could improve interventions designed to prevent and control the country''s leading chronic, infectious, environmental, and occupational diseases. OPHG''s efforts focus on conducting population-based genomic research, assessing the role of family health history in disease risk and prevention, supporting a systematic process for evaluating genetic tests, translating genomics into public health research and programs, and strengthening capacity for public health genomics in disease prevention programs. Goals: To improve public health interventions of diseases of major public health importance, including chronic, infectious, environmental, and occupational diseases, through six major initiatives: * Evaluation of Genomic Applications in Practice and Prevention (EGAPP), * Human Genome Epidemiology Network (HuGENet), * NHANES Collaborative Genomics Project, * Family History Public Health Initiative, * Genomics Translation Research and Programs, and, * Genomic Applications in Practice and Prevention Network (GAPPNet).
Proper citation: Public Health Genomics (RRID:SCR_006462) Copy
Collects, maintains and distributes Drosophila melanogaster strains for research. Emphasis is placed on genetic tools that are useful to a broad range of investigations. These include basic stocks of flies used in genetic analysis such as marker, balancer, mapping, and transposon-tagging strains; mutant alleles of identified genes, including a large set of transposable element insertion alleles; defined sets of deficiencies and a variety of other chromosomal aberrations; engineered lines for somatic and germline clonal analysis; GAL4 and UAS lines for targeted gene expression; enhancer trap and lacZ-reporter strains with defined expression patterns for marking tissues; and a collection of transposon-induced lethal mutations.
Proper citation: Bloomington Drosophila Stock Center (RRID:SCR_006457) Copy
A federated data sharing platform and infrastructure that provides access to real-time clinical, imaging and biospecimen data across jurisdictions, institutions and diseases. The web-based platform provides a secure infrastructure that advances health research by linking privacy-protected and ethically approved data among a wide network of health collaborators. Access to de-identified health records data is granted to authorized researchers after an application process so patient privacy and intellectual property are protected. BioGrid Australia''s approved researchers are provided access to multiple institutional databases, via the BioGrid interface, preventing gaps in patient records and research analysis. This legal and ethical arrangement with participating collaborators allows BioGrid to connect data through a common platform where data governance and access is managed by a highly skilled team. Data governance, security and ethics are at the core of BioGrid''s federated data sharing platform that securely links patient level clinical, biospecimen, genetic and imaging data sets across multiple sites and diseases for the purpose of medical research. BioGrid''s infrastructure and data management strategies address the increasing need by authorized researchers to dynamically extract and analyze data from multiple sources whilst protecting patient privacy. BioGrid has the capability to link data with other datasets, produce tailored reports for auditing and reporting and provide statistical analysis tools to conduct more advanced research analysis. In the health sector, BioGrid is a trusted independent virtual real-time data repository. Government investment in BioGrid has facilitated a combination of technology, collaboration and ethics approval processes for data sharing that exist nowhere else in the world.
Proper citation: BioGrid Australia (RRID:SCR_006334) Copy
http://www.niaid.nih.gov/topics/alps/Pages/default.aspx
A disease-related portal about Autoimmune Lymphoproliferative Syndrome (ALPS) including research in the following categories: Medical and Genetic Description, Database of Mutations, Database of ALPS-FAS Mutations, and Molecular Pathways. Autoimmune Lymphoproliferative Syndrome (ALPS) is a recently recognized disease in which a genetic defect in programmed cell death, or apoptosis, leads to breakdown of lymphocyte homeostasis and normal immunologic tolerance. It is an inherited disorder of the immune system that affects both children and adults. In ALPS, unusually high numbers of white blood cells called lymphocytes accumulate in the lymph nodes, liver, and spleen, which can lead to enlargement of these organs. Database of Mutations * All existing ALPS-FAS mutations (NIH Web site) * ALPS-FAS * ALPS Type Ia (most common type) ** Reported FAS (TNFRSF6) mutations causing ALPS ** Distribution of FAS (TNFRSF6) mutations ** FAS (TNFRSF6) polymorphisms * ALPS Type II
Proper citation: Autoimmune Lymphoproliferative Syndrome Information (RRID:SCR_006451) Copy
http://buridan.sourceforge.net/
Open source software written in R that tracks a single animal walking in a homogenous environment (Buritrack) and analyzes its trajectory. It extracts eleven metrics and includes correlation analyses and a Principal Components Analysis (PCA). It was designed to be easily customized to personal requirements. In combination with inexpensive hardware, these tools can readily be used for teaching and research purposes. Buritrack is a program to track individual Drosophila fruit flies online with any camera as they walk in Buridan's paradigm. The program extracts the coordinate locations of the fly and stores them in a text file.
Proper citation: Centroid Trajectory Analysis (RRID:SCR_006331) Copy
The Transverse Myelitis Association was established in 1994 as an organization dedicated to advocacy for those who have these rare neuroimmunologic diseases. It was incorporated as a not-for-profit organization in 1996. It facilitates support and networking opportunities amongst families; provides educational information; functions as a clearinghouse for articles and research literature; and investigates, advocates for and supports research and innovative treatment efforts. Transverse Myelitis is a rare neurological disorder that is part of a spectrum of neuroimmunologic diseases of the central nervous system. Other disorders in this spectrum include, Acute Disseminated Encephalomyelitis (ADEM), Optic Neuritis, and Neuromyelitis Optica (Devic''s disease). The membership of The Transverse Myelitis Association includes persons with all of these disorders, their family members and caregivers and the medical professionals who treat people with these disorders. The TMA publishes a newsletter for our members twice a year, which contains articles by physicians and health care providers. There are also articles written by people with the rare neuroimmunologic disorders. A membership directory is published and distributed annually. The TMA assists in the development of local support groups and is involved in various fund-raising efforts, such as Reading for Rachel, to raise awareness and funds for research. The TMA supports and conducts various symposiums and workshops involving both professionals and patients for the exchange of information regarding research and treatment strategies for persons with the rare neuroimmunologic disorders of the central nervous system.
Proper citation: Transverse Myelitis Association (RRID:SCR_006523) Copy
http://podb.nibb.ac.jp/Organellome/
Database of images, movies, and protocols to promote a comprehensive understanding of plant organelle dynamics, including organelle function, biogenesis, differentiation, movement, and interactions with other organelles. It consists of 5 individual parts, ''Perceptive Organelles Database'', ''The Organelles Movie Database'', ''The Organellome Database'', ''The Functional Analysis Database'', and ''External Links to other databases and Web pages''. All the data and protocols in ''The Organelle Movie Database'', ''The Organellome Database'' and ''The Functional Analysis Database'' are populated by direct submission of experimentally determined data from plant researchers. Your active contributions by submission of data and protocols to our database would also be appreciated. * Perceptive Organelles Database: This database contains images and movies of organelles in various tissues during different developmental stages in response to environmental stimuli. * Organelles Movie Database: This database contains time-lapse images, Z slices and projection images of organelles in various tissues during different developmental stages, visualized using fluorescent and non-fluorescent probes. * Organellome Database: This database contains images for cellular structures that are composed of organelle images in various tissues during different developmental stages, visualized with fluorescent and non-fluorescent probes. * Functional Analysis Database: This database is a collection of protocols for plant organelle research. * External Links: Access to biological databases.
Proper citation: Plant Organelles Database (RRID:SCR_006520) Copy
http://www.informatics.jax.org/searches/GO_form.shtml
With the MGI GO Browser, you can search for a GO term and view all mouse genes annotated to the term or any subterms. You can also browse the ontologies to view relationships between terms, term definitions, as well as the number of mouse genes annotated to a given term and its subterms. The MGI GO browser directly accesses the GO data in the MGI database, which is updated nightly. Platform: Online tool
Proper citation: MGI GO Browser (RRID:SCR_006489) Copy
http://www.fda.gov/ScienceResearch/BioinformaticsTools/Arraytrack/default.htm
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. Software tool developed for ArrayTrack that takes a list of genes and identifies terms in Gene Ontology associated with those genes. GOFFA provides tools to view/access the following: GO term hierarchy, full listing of GO terms annotated with the genes associated with a given term, Fisher's exact test p-value providing the probability of identifying that many genes for a given term by chance alone, and relative enrichment factor (E-value) giving the enrichment of a GO term for genes in the submitted list relative to the frequency of genes assigned to that term from the full set of GOFFA annotated genes for a particular species.
Proper citation: Gene Ontology For Functional Analysis (GOFFA) (RRID:SCR_006484) Copy
Collection of chemical structures. Provides access to structures, properties and associated information from hundreds of data sources to find compounds of interest and provides services to improve this data by curation and annotation and to integrate it with users applications.
Proper citation: ChemSpider (RRID:SCR_006360) Copy
A fungal rDNA internal transcribed spacer (ITS) sequence database (although additional genes and genetic markers are also welcome) to facilitate identification of environmental samples of fungal DNA. Additional important features include user annotation of INSD sequences to add metadata on, e.g., locality, habitat, soil, climate, and interacting taxa. The user can furthermore annotate INSD sequences with additional species identifications that will appear in the results of any analyses done. UNITE focuses on high-quality ITS sequences generated from fruiting bodies collected and identified by experts and deposited in public herbaria. In addition, it also holds all fungal ITS sequences in the International Nucleotide Sequence Databases (INSD: NCBI, EMBL, DDBJ). Both sets of sequences may be used in any analyses carried out. UNITE is accompanied by a project management system called PlutoF, where users can store field data, document the sequencing lab procedures, manage sequences, and make analyses. PlutoF intends to make it possible for taxonomists, ecologists, and biogeographers to use a common platform for data storage, handling, and analyses, with the intent of facilitating an integration of these disciplines. A user can have an unlimited number of projects but still make analyses across any project data available to him.
Proper citation: UNITE (RRID:SCR_006518) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Project to advance understanding of the neural mechanisms of vocal learning by providing a quantitative description of the relationship between physiological variables and vocal performance over the course of development in a songbird, the zebra finch. They propose to study vocal learning dynamically across neuronal and peripheral subsystems, using a novel collaborative approach that will harness the combined expertise of several investigators. Their proposed research model will 1) provide simultaneous measurements of acoustic, articulatory and electrophysiological data that will document the detailed dynamics of the vocal imitation process in a standardized learning paradigm; and 2) incorporate these measurements into a theoretical/computational framework that simultaneously provides a phenomenological description and attempts to elucidate the mechanistic basis of the learning process.
Proper citation: Zebra Finch Song Learning Consortium (RRID:SCR_006356) Copy
Web server to identify statistically enriched pathways, diseases, and GO terms for a set of genes or proteins, using pathway, disease, and GO knowledge from multiple famous databases. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). A standalone command line version is also available, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: KOBAS (RRID:SCR_006350) Copy
A production service that gives researchers the ability to create and manage long-term identifiers so that they can to track usage, get credit for their work, share their data, and have the data reused for additional research. As a result, EZID identifiers also make it possible to increase citations, to build on previous work, to conduct new research, and avoid duplicating previous efforts. EZID identifiers provide a simple but powerful way to track research materials, including datasets, throughout their life cycle. In this way, researchers can share their data, get more citations, and track their results.
Proper citation: EZID (RRID:SCR_006473) Copy
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