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http://www.med.harvard.edu/AANLIB/
An atlas of normal and abnormal brain images intended as an introduction to basic neuroanatomy, with emphasis on the pathoanatomy of several leading central nervous system diseases that integrates clinical information with magnetic resonance (MR), x-ray computed tomography (CT), and nuclear medicine images. A range of brain abnormalities are presented including examples of certain brain disease presented with various combinations of image type and imaging frequency. Submissions of concise, exemplary, clinically driven examples of neuroimaging are welcome.
Proper citation: Whole Brain Atlas (RRID:SCR_005390) Copy
Repository for all research outputs from across all fields of science in any file format as well as both positive and negative results. They assign all publicly available uploads a Digital Object Identifier (DOI) to make the upload easily and uniquely citeable. They further support harvesting of all content via the OAI-PMH protocol. They promote peer-reviewed openly accessible research, and curate uploads. ZENODO allows users to create their own collection and accept or reject all uploads to it. They allow for uploading under a multitude of different licenses and access levels.
Proper citation: ZENODO (RRID:SCR_004129) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023.Digital collection of images, with themes ranging from medical and social history to contemporary healthcare and biomedical science. The collection contains historical images from the Wellcome Library collections, Tibetan Buddhist paintings, ancient Sanskrit manuscripts written on palm leaves, beautifully illuminated Persian books and much more. The Biomedical Collection holds over 40 000 high-quality images from the clinical and biomedical sciences. Selected from the UK''s leading teaching hospitals and research institutions, it covers disease, surgery, general healthcare, sciences from genetics to neuroscience including the full range of imaging techniques. They are always looking for new high quality biomedical images from scientific researchers, clinical photographers and artists in any field of science or medicine. As a contributor you retain your original material and copyright, and receive commission and full credit each time your images are used. The annual Wellcome Images awards (previously known as Biomedical Images Awards) reward contributors for their outstanding work and winners are chosen by a panel of experts. The resulting public exhibitions are always extremely popular and receive widespread acclaim. All images on the Wellcome Images site are available free for use in: * private study and non-commercial research * examination papers * criticism and review, this applies only where there are no multiple copies made * theses submitted by a student at a higher or further education institution for the purposes of securing a degree * personal use by private individuals
Proper citation: Wellcome Images (RRID:SCR_004181) Copy
http://www.fishbase.org/home.htm
A global species database and encyclopedia of over 32,800 species and subspecies of fishes that is searchable by common name, genus, species, geography, family, ecosystem, references literature, tools, etc. It links to other, related databases such as the Catalog of Fishes, GenBack, and LarvalBase. It is associated with a partner journal, Acta Ichthyologica et Piscatoria. It is available in English, Greek, Spanish, Portuguese, French, Dutch, Italian, and German. Photo and video submissions are welcome. FishBase 2004 is also available on DVD or CD-ROMs with full information on 28,500 species. It comes together with the FishBase 2000 book and can be ordered for 95 US$ including air-mail.
Proper citation: FishBase (RRID:SCR_004376) Copy
Database of images of putative biological pathways, macromolecular structures, gene families, and cellular relationships. It is of use to those who are working with large sets of genes or proteins using cDNA arrays, functional genomics, or proteomics. The rationale for this collection is that: # Except in a few cases, information on most biological pathways in higher eukaryotes is non-existent, incomplete, or conflicting. # Similar biological pathways differ by tissue context, developmental stages, stimulatory events, or for other complex reasons. This database allows comparisons of different variations of pathways that can be tested empirically. # The goal of this database is to use images created directly by biomedical scientists who are specialists in a particular biological system. It is specifically designed to NOT use average, idealized or redrawn pathways. It does NOT use pathways defined by computer algorithm or information search approaches. # Information on biological pathways in higher eukaryotes generally resides in the images and text of review papers. Much of this information is not easily accessible by current medical reference search engines. # All images are attributable to the original authors. All pathways or other biological systems described are graphic representations of natural systems. Each pathway is to be considered a work in progress. Each carries some degree of error or incompleteness. The end user has the ultimate responsibility to determine the scientific correctness and validity in their particular biological system. Image/pathway submissions are welcome.
Proper citation: Biological Biochemical Image Database (RRID:SCR_003474) Copy
An NSF supported image repository of over 374,000 high-resolution photographs of approximately 4,000 species for research and education, used largely but not exclusively in the area of biodiversity research. Images can be annotated by users and browsed by specimen, view, taxonomy, location, collection, or annotation.
Proper citation: MorphBank (RRID:SCR_003147) Copy
https://www.tgh.org/institutes-and-services/cancer-institute/precision-medicine-bio-repository
Procures high-quality biologic specimens along with coded clinical and demographic data across broad ethnic, racial, and social demographic of patients. All specimens are systematically collected and processed so that their multi-functional potential for recovering high-quality bioanalytes (including RNA, genomic DNA, protein, enzymes and metabolites) is conserved. All specimens are stored and protected in a database hub to connect researchers conducting variety of scientific projects across multiple medical specialties. Muilti-disciplinary biorepository with capacity for generating specialized bioanalytes.
Proper citation: Tampa General Hospital-University of South Florida Health Precision Medicine Biorepository (RRID:SCR_027501) Copy
Platform to facilitate sharing, discovery, and secure access to UCSF biomedical data. It''s powered by the Dataverse Network platform, which supports a variety of data types, as well as attribution and licensing needs. Researchers may share datasets, discover data from other labs, and reuse data. Links to tools and information that help scientists properly organize, manage, and document their datasets are also provided.
Proper citation: UCSF DataShare (RRID:SCR_004340) Copy
http://www.physionet.org/physiotools/
Growing library of software for physiologic signal processing and analysis, detection of physiologically significant events using both classical techniques and novel methods based on statistical physics and nonlinear dynamics, interactive display and characterization of signals, creation of new databases, simulation of physiologic and other signals, quantitative evaluation and comparison of analysis methods, and analysis of nonequilibrium and nonstationary processes. A unifying theme of the research projects that contribute software to PhysioToolkit is the extraction of hidden information from biomedical signals, information that may have diagnostic or prognostic value in medicine, or explanatory or predictive power in basic research. Contributions of software to PhysioToolkit are welcome, http://physionet.org/guidelines.shtml#software-contributions
Proper citation: PhysioToolkit (RRID:SCR_006868) Copy
Cancer research platform that aggregates clinical, genomic and functional data from various types of patient derived cancer models, xenographs, organoids and cell lines. Open catalog of harmonised patient-derived cancer models. Standardises, harmonises and integrates clinical metadata, molecular and treatment-based data from academic and commercial providers worldwide. Data is FAIR and underpins generation and testing of new hypotheses in cancer mechanisms and personalised medicine development. PDCM Finder have expanded to organoids and cell lines and is now called CancerModels.Org. PDCM Finder was launched in April 2022 as successor of PDX Finder portal, which focused solely on patient-derived xenograft models.
Proper citation: CancerModels.Org (RRID:SCR_023931) Copy
Repository for distribution of various types of molecular data from human, cell-based and animal model biosamples, analytical results and research tools generated through multiple NIA-supported programs. Currently Portal supports AMP-AD Target Discovery and Preclinical Validation and MOVE-AD Consortia and translational center, MODEL-AD.
Proper citation: AMP-AD Knowledge Portal (RRID:SCR_016316) Copy
Free cloud platform for secure neuroscience data analysis. Allows to manage data, processing and results, sharing projects privately with collaborators or publicly with brainlife.io community.Promotes engagement and education in reproducible neuroscience.You can share your neuroimaging data publicly or privately. Data on brainlife.io is organized as Datatypes to allow interoperability between Apps.
Proper citation: brainlife (RRID:SCR_020940) Copy
Database for the identification of the human proteome and its use across the scientific community. Users can browse proteins and chromosomes and contribute to the data repository.
Proper citation: ProteomicsDB (RRID:SCR_015562) Copy
https://research.bidmc.org/biodatabank-core
Core at BIDMC is a physical biorepository of deeply phenotyped human specimens that are linked to clinical diagnoses, a digital databank of omics and histological profiling generated from stored and annotated samples, and a virtual catalogue interface that will facilitate collaborations with the aim to catalyze innovative biomedical research and discovery. Goal of the BioDataBank Core is to build a biobank of Beth Israel Deaconess Medical Center (BIDMC)/BILH patient biospecimens & Omics data from our four Translational Research Hubs that are linked to clinical data for biomedical research directed towards advancing precision medicine. We will diversify the targeted biobank populations by engaging and collaborating with Beth Israel Lahey Health (BILH)-associated community health centers.
Proper citation: Beth Israel Deaconess Medical Center BioDataBank Core Facility (RRID:SCR_028860) Copy
http://www.uchicagoddrcc.org/research-cores/integrated-translational-research-core
Core that serves as both a central repository for all the samples and data shared by the other cores and a catalyst for interdisciplinary research.
Proper citation: University of Chicago Digestive Diseases Research Core Center Integrated Translational Research Core (RRID:SCR_015606) Copy
A comprehensive index for locating and compiling bioinformatics and online science tools. Users can browse, rate, share and save various tools listed in the LabWorm repository. Resources contain a short description, a list of related sites, comments, a list of users who have shared and rated the resource, and the main site URL. Resources may be saved to a personal toolbox collection. User news feeds can be customized to include new scientific literature from journals of choice. Users who want to utilize LabWorm tools to improve their own website can access the alternate Developer site.
Proper citation: LabWorm (RRID:SCR_014079) Copy
An open-source, web-based platform and suite of software tools for for sharing heterogeneous scientific research datasets, models or simulations, processes and research outcomes - and collaborations between scientists. It preserves associations between them, along with information about the people and organizations involved. Underpinning SEEK is the ISA infrastructure, a standard format for describing how individual experiments are aggregated into wider studies and investigations. Within SEEK, ISA has been extended and is configurable to allow the structure to be used outside of Biology. SEEK is incorporating semantic technology allowing sophisticated queries over the data, yet without getting in the way of your users. Access to the RESTful API to access the data within SEEK is available.
Proper citation: SEEK (RRID:SCR_002651) Copy
Portal for dataset discovery across a heterogeneous, distributed group of transcriptomics, genomics, proteomics and metabolomics data resources. These resources span eight repositories in three continents and six organisations, including both open and controlled access data resources.
Proper citation: Omics Discovery Index (RRID:SCR_010494) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented Jan 13, 2022; To enhance the understanding of the evolution of the Kingdom Fungi, 1500+ species were sampled for eight gene loci across all major fungal clades, plus a subset of taxa for a suite of morphological and ultrastructural characters with resulting data: AFTOL Molecular Database (generated by WASABI - Web Accessible Sequence Analysis for Biological Inference), Blast search the AFTOL Database (generated by WASABI), AFTOL primers (generated by WASABI), AFTOL primers by species (generated by WASABI), AFTOL alignments, and the AFTOL Structural and Biochemical Database. Users may submit samples to the AFTOL project. AFTOL is a collaboration centered around four universities in the United States: Duke University (Francois Lutzoni and Rytas Vilgalys), Clark University (David Hibbett), Oregon State University (Joey Spatafora), and University of Minnesota (David McLaughlin). Participants throughout the world have donated vouchers, taxon samples, and gene sequences. The aim of the project is to reconstruct the fungal tree of life using all available data for eight loci (nuclear ribosomal DNA: LSU, SSU, ITS (including 5.8s, ITS1 and ITS2); RNA polymerase II: RPB1, RPB2; elongation factor 1-alpha; mitochondrial SSU rDNA, and mitochondrial ATP synthase protein subunit 6). A further objective of this study is to summarize and integrate current knowledge regarding fungal subcellular features within this new phylogenetic framework. The name of the bioinformatic package developed for AFTOL is WASABI which provides an efficient communication platform to facilitate the collection and dissemination of molecular data to (and from) the laboratories and participants. All molecular data can be viewed, downloaded, verified, and corrected by the participants of AFTOL. A central goal of the WASABI interface is to establish an automated analysis framework that includes basecalling of newly generated chromatograms, contig assembly, quality verification of sequences (including a local BLAST), sequence alignment, and congruence test. Gene sequences that pass all tests and are finally verified by their authors will undergo automated phylogenetic analysis on a regular schedule. Although all steps are initially carried out noninteractively, the users can verify and correct the results at any step and thus initiate the reanalysis of dependent data.
Proper citation: AFTOL (RRID:SCR_004650) Copy
The Deciphering Developmental Disorders (DDD) study aims to find out if using new genetic technologies can help doctors understand why patients get developmental disorders. To do this we have brought together doctors in the 23 NHS Regional Genetics Services throughout the UK and scientists at the Wellcome Trust Sanger Institute, a charitably funded research institute which played a world-leading role in sequencing (reading) the human genome. The DDD study involves experts in clinical, molecular and statistical genetics, as well as ethics and social science. It has a Scientific Advisory Board consisting of scientists, doctors, a lawyer and patient representative, and has received National ethical approval in the UK. Over the next few years, we are aiming to collect DNA and clinical information from 12,000 undiagnosed children in the UK with developmental disorders and their parents. The results of the DDD study will provide a unique, online catalogue of genetic changes linked to clinical features that will enable clinicians to diagnose developmental disorders. Furthermore, the study will enable the design of more efficient and cheaper diagnostic assays for relevant genetic testing to be offered to all such patients in the UK and so transform clinical practice for children with developmental disorders. Over time, the work will also improve understanding of how genetic changes cause developmental disorders and why the severity of the disease varies in individuals. The Sanger Institute will contribute to the DDD study by performing genetic analysis of DNA samples from patients with developmental disorders, and their parents, recruited into the study through the Regional Genetics Services. Using microarray technology and the latest DNA sequencing methods, research teams will probe genetic information to identify mutations (DNA errors or rearrangements) and establish if these mutations play a role in the developmental disorders observed in patients. The DDD initiative grew out of the groundbreaking DECIPHER database, a global partnership of clinical genetics centres set up in 2004, which allows researchers and clinicians to share clinical and genomic data from patients worldwide. The DDD study aims to transform the power of DECIPHER as a diagnostic tool for use by clinicians. As well as improving patient care, the DDD team will empower researchers in the field by making the data generated securely available to other research teams around the world. By assembling a solid resource of high-quality, high-resolution and consistent genomic data, the leaders of the DDD study hope to extend the reach of DECIPHER across a broader spectrum of disorders than is currently possible.
Proper citation: Deciphering Developmental Disorders (RRID:SCR_006171) Copy
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