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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.
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
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
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
https://github.com/EpistasisLab/ReBATE
Open source software Python package to compare relief based feature selection algorithms used in data mining. Used for feature selection in any bioinformatics problem with potentially predictive features and target outcome variable, to detect feature interactions without examination of all feature combinations, to detect features involved in heterogeneous patterns of association such as genetic heterogeneity .
Proper citation: ReBATE (RRID:SCR_017139) Copy
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
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
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
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
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
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
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
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
https://github.com/humanlongevity/HLA
Software tool for fast and accurate HLA typing from short read sequence data. Iteratively refines mapping results at amino acid level to achieve four digit typing accuracy for both class I and II HLA genes, taking only 3 min to process 30× whole genome BAM file on desktop computer.
Proper citation: xHLA (RRID:SCR_022277) Copy
https://github.com/BioDepot/nbdocker
Software tool as Jupyter Notebook extension for Docker. Each Docker container encapsulates its individual computing environment to allow different programming languages and computing environments to be included in one single notebook, provides user to document code as well as computing environment.
Proper citation: nbdocker (RRID:SCR_017159) Copy
https://github.com/aametwally/Metabolic_Subphenotype_Predictor
Software repository contains code for Inference of T2D metabolic subphenotypes (MuscleIR, Beta-cell Function, Incretin Effect, Hepatic IR), Identification of dominant metabolic subphenotype, Feature extraction from glucose tiemseries, Extraction of reduced representation of glucose tiemseries,Visualization of metabolic phenotypes based on various glucose-related metrics,Concordance between CGM and Venous glucose values from at home and at clinical setting, Classification of metabolic subphenotypes.
Proper citation: Metabolic Subphenotype Predictor (RRID:SCR_027192) Copy
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
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
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
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
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
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