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http://snyderome.stanford.edu/

Data set generated by personal omics profiling of Dr. Michael Snyder at Stanford University. It combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. The analysis revealed various medical risks, including type II diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions.

Proper citation: iPOP (RRID:SCR_008991) Copy   

•   Source: SciCrunch Registry

http://evs.gs.washington.edu/EVS/

The goal of the project is to discover novel genes and mechanisms contributing to heart, lung and blood disorders by pioneering the application of next-generation sequencing of the protein coding regions of the human genome across diverse, richly-phenotyped populations and to share these datasets and findings with the scientific community to extend and enrich the diagnosis, management and treatment of heart, lung and blood disorders. The groups participating and collaborating in the NHLBI GO ESP include: Seattle GO - University of Washington, Seattle, WA Broad GO - Broad Institute of MIT and Harvard, Cambridge, MA WHISP GO - Ohio State University Medical Center, Columbus, OH Lung GO - University of Washington, Seattle, WA WashU GO - Washington University, St. Louis, MO Heart GO - University of Virginia Health System, Charlottesville, VA ChargeS GO - University of Texas Health Sciences Center at Houston

Proper citation: NHLBI Exome Sequencing Project (ESP) (RRID:SCR_012761) Copy   

•   Source: SciCrunch Registry

https://pypi.org/project/pmlb/

Python wrapper for Penn Machine Learning Benchmark data repository. Large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms. Part of PyPI https://pypi.org/

Proper citation: Penn machine learning benchmark repository (RRID:SCR_017138) Copy   

•   Source: SciCrunch Registry

https://maayanlab.cloud/drugmonizome/#/

Database with search engine for querying annotated sets of drugs and small molecules for performing drug set enrichment analysis.

Proper citation: Drugmonizome (RRID:SCR_024821) Copy   

•   Source: SciCrunch Registry

http://life.ccs.miami.edu/life/

LIFE search engine contains data generated from LINCS Pilot Phase, to integrate LINCS content leveraging semantic knowledge model and common LINCS metadata standards. LIFE makes LINCS content discoverable and includes aggregate results linked to Harvard Medical School and Broad Institute and other LINCS centers, who provide more information including experimental conditions and raw data. Please visit LINCS Data Portal.

Proper citation: LINCS Information Framework (RRID:SCR_003937) Copy   

•   Source: SciCrunch Registry

http://proteomics.ucsd.edu/Software/NeuroPedia/index.html

A neuropeptide encyclopedia of peptide sequences (including genomic and taxonomic information) and spectral libraries of identified MS/MS spectra of homolog neuropeptides from multiple species.

Proper citation: NeuroPedia (RRID:SCR_001551) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   

•   Source: SciCrunch Registry

http://www.mitomap.org/

Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf.

Proper citation: MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/cardiovascularproteomics/

The Cardiovascular Proteomics Center is a research center funded by the NIH/NHLBI to analyze and identify proteins that may be modified or created by oxidative stress. The CPC is developing and applying new proteomics methodology and instrumentation to the analysis of known proteins and those yet to be discovered.

Proper citation: Cardiovascular Proteomics Center (RRID:SCR_000603) Copy   

•   Source: SciCrunch Registry

http://rdp.cme.msu.edu

A database which provides ribosome related data services to the scientific community, including online data analysis, rRNA derived phylogenetic trees, and aligned and annotated rRNA sequences. It specifically contains information on quality-controlled, aligned and annotated bacterial and archaean 16S rRNA sequences, fungal 28S rRNA sequences, and a suite of analysis tools for the scientific community. Most of the RDP tools are now available as open source packages for users to incorporate in their local workflow.

Proper citation: Ribosomal Database Project (RRID:SCR_006633) Copy   

•   Source: SciCrunch Registry

https://lincsportal.ccs.miami.edu/signatures/home

Primary access point for compendium of LINCS data with substantial changes in data architecture and APIs, completely redesigned user interface, and enhanced curated metadata annotations to support more advanced, intuitive and deeper querying, exploration and analysis capabilities. LINCS datasets are accessible at data point level enabling users to directly access and download any subset of signatures across entire library independent from originating source, project or assay. Newly designed query interface enables global metadata search with autosuggest across all annotations associated with perturbations, model systems, and signatures.

Proper citation: LINCS Data Portal 2.0 (RRID:SCR_022566) Copy   

•   Source: SciCrunch Registry

https://appyters.maayanlab.cloud

Collection of web-based software applications that enable users to execute bioinformatics workflows without coding. Turns Jupyter notebooks into fully functional standalone web-based bioinformatics applications. Each Appyter application introduces data entry form for uploading or fetching data, as well as for selecting options for various settings. Once user presses Submit, Appyter is executed in cloud and user is presented with Jupyter Notebook report that contain results. Report includes markdown text, interactive and static figures, and source code. Appyter users can share the link to the output report, as well as download the fully executable notebook for execution on other platforms.

Proper citation: Appyters (RRID:SCR_021245) Copy   

•   Source: SciCrunch Registry

https://www.accordtrial.org/public

Study testing whether strict glucose control lowers the risk of heart disease and stroke in adults with type 2 diabetes. In addition the study is exploring: 1) Whether in the context of good glycemic control the use of different lowering lipid drugs will further improve these outcomes and 2) If strict control of blood pressure will also have additional beneficial effects on reducing cardiovascular disease. The design was a randomized, multicenter, double 2 X 2 factorial trial in 10,251 patients with type 2 diabetes mellitus. It was designed to test the effects on major CVD events of intensive glycemia control, of fibrate treatment to increase HDL-cholesterol and lower triglycerides (in the context of good LDL-C and glycemia control), and of intensive blood pressure control (in the context of good glycemia control), each compared to an appropriate control. All 10,251 participants were in an overarching glycemia trial. In addition, one 2 X 2 trial addressed the lipid question in 5,518 of the participants and the other 2 X 2 trial addressed the blood pressure question in 4,733 of the participants. The glycemia trial was terminated early due to higher mortality in the intensive compared with the standard glycemia treatment strategies. The results were published in June 2008 (N Eng J Med 2008;358:2545-59). Study-delivered treatment for all ACCORD participants was stopped on June 30, 2009, and the participants were assisted as needed in transferring their care to a personal physician. The lipid and blood pressure results (as well as the microvascular outcomes and eye substudy results) were published in 2010. All participants are continuing to be followed in a non-treatment observational study.

Proper citation: ACCORD (RRID:SCR_009015) Copy   

•   Source: SciCrunch Registry

http://lincsportal.ccs.miami.edu/dcic-portal/

Portal which provides a unified interface for searching LINCS dataset packages and reagents. Users can use the portal to access datasets, small molecules, cells, genes, proteins and peptides, and antibodies.

Proper citation: LINCS Data Portal (RRID:SCR_014939) Copy   

•   Source: SciCrunch Registry

https://medicine.yale.edu/keck/nida/yped/

Open source system for storage, retrieval, and integrated analysis of large amounts of data from high throughput proteomic technologies. YPED currently handles LCMS, MudPIT, ICAT, iTRAQ, SILAC, 2D Gel and DIGE. The repository contains data sets which have been released for public viewing and downloading by the responsible Primary Investigators. It includes proteomic data generated by the Yale NIDA Neuroproteomics Center (http://medicine.yale.edu/keck/nida/index.aspx). Sample descriptions are compatible with the evolving MIAPE standards.

Proper citation: YPED (RRID:SCR_001436) Copy   

•   Source: SciCrunch Registry

http://www.tarp.nih.gov/

Trans-NIH program encouraging and facilitating the study of the underlying mechanisms controlling blood vessel growth and development. Other aims include: to identify specific targets and to develop therapeutics against pathologic angiogenesis in order to reduce the morbidity due to abnormal blood vessel proliferation in a variety of disease states; to better understand the process of angiogenesis and vascularization to improve states of decreased vascularization; to encourage and facilitate the study of the processes of lymphangiogenesis; and to achieve these goals through a multidisciplinary approach, bringing together investigators with varied backgrounds and varied interests.

Proper citation: Trans-Institute Angiogenesis Research Program (RRID:SCR_000384) Copy   

•   Source: SciCrunch Registry

http://www.cvrgrid.org/

Infrastructure for sharing cardiovascular data and data analysis tools. Human ExVivo heart data set and canine ExVivo normal and failing heart data sets are available. Canine hearts atlas and human InVivo atlases are available.

Proper citation: CardioVascular Research Grid (CVRG) (RRID:SCR_004472) Copy   

•   Source: SciCrunch Registry

http://www.macaque.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on June 8, 2020.Macaque genomic and proteomic resources and how they are providing important new dimensions to research using macaque models of infectious disease. The research encompasses a number of viruses that pose global threats to human health, including influenza, HIV, and SARS-associated coronavirus. By combining macaque infection models with gene expression and protein abundance profiling, they are uncovering exciting new insights into the multitude of molecular and cellular events that occur in response to virus infection. A better understanding of these events may provide the basis for innovative antiviral therapies and improvements to vaccine development strategies.

Proper citation: Macaque.org (RRID:SCR_002767) Copy   

•   Source: SciCrunch Registry

http://www.mybiosoftware.com/population-genetics/332

A tool for SNP Search and downloading with local management. It also offers flanking sequence downloading and automatic SNP filtering. It requires Windows and .NET Framework.

Proper citation: SNPHunter (RRID:SCR_002968) Copy   

•   Source: SciCrunch Registry

http://sig.biostr.washington.edu/projects/fm/

A domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy. It is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems. Its ontological framework can be applied and extended to all other species. The description of how the OWL version was generated is in Pushing the Envelope: Challenges in a Frame-Based Representation of Human Anatomy by N. F. Noy, J. L. Mejino, C. Rosse, M. A. Musen: http://bmir.stanford.edu/publications/view.php/pushing_the_envelope_challenges_in_a_frame_based_representation_of_human_anatomy The Foundational Model of Anatomy ontology has four interrelated components: # Anatomy taxonomy (At), # Anatomical Structural Abstraction (ASA), # Anatomical Transformation Abstraction (ATA), # Metaknowledge (Mk), The ontology contains approximately 75,000 classes and over 120,000 terms; over 2.1 million relationship instances from over 168 relationship types link the FMA's classes into a coherent symbolic model.

Proper citation: FMA (RRID:SCR_003379) Copy   

•   Source: SciCrunch Registry