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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://apps.cytoscape.org/apps/stringapp
Software application for network analysis and visualization of proteomics data. Cytoscape app that makes it easy to import STRING networks into Cytoscape, retains appearance and many of features of STRING, and integrates data from associated databases.
Proper citation: Cytoscape StringApp (RRID:SCR_025009) Copy
Software framework to find and re-analyze public Mass Spectrometry data. Used to find uniformly formatted public MS/MS data in the Global Natural Product Social Molecular Networking Platform (GNPS) via formatted metadata. New or previously collected data can be added provided they adhere to the ReDU metadata standards (the implemented drag-and-drop validator is applicable to any scientific data) and data are available in GNPS/MassIVE.
Proper citation: ReDU (RRID:SCR_025105) Copy
https://fmug.amaral.northwestern.edu/
Software data-driven tool to identify understudied genes and characterize their tractability. Users submit list of human genes and can filter these genes down based on list of factors. Code to generate Find My Understudied Genes app for Windows, iOS and macOS platforms.
Proper citation: Find My Understudied Genes (RRID:SCR_025047) Copy
https://hdpm.biomedinfolab.com/netmage/
Web tool for automated generation of interactive disease-disease network visualizations given input PheWAS summary data. Given genetic associations from Phenome-Wide Association Study, disease-disease network can be constructed where nodes represent phenotypes and edges represent shared genetic associations between phenotypes.
Proper citation: NETMAGE (RRID:SCR_021843) Copy
https://github.com/SciKnowEngine/kefed.io
Knowledge engineering software for reasoning with scientific observations and interpretations. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a "neural connection matrix" interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. The KEfED model is designed to provide a lightweight representation for scientific knowledge that is (a) generalizable, (b) a suitable target for text-mining approaches, (c) relatively semantically simple, and (d) is based on the way that scientist plan experiments and should therefore be intuitively understandable to non-computational bench scientists. The basic idea of the KEfED model is that scientific observations tend to have a common design: there is a significant difference between measurements of some dependent variable under conditions specified by two (or more) values of some independent variable.
Proper citation: Knowledge Engineering from Experimental Design (RRID:SCR_001238) Copy
The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.
Proper citation: LONI MiND (RRID:SCR_004820) Copy
http://scicrunch.org/resources
Portal providing identifiers for Antibodies, Model Organisms, and Tools (software, databases, services) created in support of the Resource Identification Initiative, which aims to promote research resource identification, discovery, and reuse. The portal offers a central location for obtaining and exploring Research Resource Identifiers (RRIDs) - persistent and unique identifiers for referencing a research resource. A critical goal of the RII is the widespread adoption of RRIDs to cite resources in the biomedical literature and other places that reference their generation or use. RRIDs use established community identifiers where they exist, and are cross-referenced in their system where more than one identifier exists for a single resource.
Proper citation: Resource Identification Portal (RRID:SCR_004098) Copy
http://probalign.njit.edu/probalign/login
Data analysis service that computes maximal expected accuracy multiple sequence alignments from partition function posterior probabilities.
Proper citation: eProbalign (RRID:SCR_013247) Copy
http://web.mit.edu/glycomics/gt/gtdb.shtml
A pathway-based graphical interface for navigating the glycoenzyme database. The goal of the project is to define the paradigms by which carbohydrate binding proteins function in cellular communication. These pages are divided into six categories: -Glycosphingolipid: Sub-categories are Isogloboseries, Globoseries, Neo-lactoseries, Lactoseries and Ganglioseries - N-linked: Sub-categories are High-mannose, Hybrid and Complex -Mucin -Terminal Core 1 -Other O-linked -Terminal All: Includes all potential terminal structures for each glycan category
Proper citation: Glycosylation Pathways Database (RRID:SCR_013486) Copy
http://web.stanford.edu/group/barres_lab/brain_rnaseq.html
Database containing RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of cerebral cortex. Collection of RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of mouse cerebral cortex. RNA-Seq of cell types isolated from mouse and human brain.
Proper citation: Brain RNA-Seq (RRID:SCR_013736) Copy
http://hb.flatironinstitute.org/
Formerly known as GIANT (Genome-scale Integrated Analysis of gene Networks in Tissues), HumanBase applies machine learning algorithms to learn biological associations from massive genomic data collections. These integrative analyses reach beyond existing "biological knowledge" represented in the literature to identify novel, data-driven associations.
Proper citation: HumanBase (RRID:SCR_016145) Copy
http://www.broadinstitute.org/pubs/MitoCarta/
Collection of genes encoding proteins with strong support of mitochondrial localization. Inventory of genes encoding mitochondrial-localized proteins and their expression across 14 mouse tissues. Database is based on human and mouse RefSeq proteins that are mapped to NCBI Gene loci. MitoCarta 2.0 inventory provides molecular framework for system-level analysis of mammalian mitochondria.
Proper citation: MitoCarta (RRID:SCR_018165) Copy
http://software.broadinstitute.org/gsea/msigdb/index.jsp
Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.
Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy
http://brainmap.wisc.edu/monkey.html
NO LONGER AVAILABLE. Documented on September 17, 2019. A set of multi-subject atlas templates to facilitate functional and structural imaging studies of the rhesus macaque. These atlases enable alignment of individual scans to improve localization and statistical power of the results, and allow comparison of results between studies and institutions. This population-average MRI-based atlas collection can be used with common brain mapping packages such as SPM or FSL.
Proper citation: Rhesus Macaque Atlases for Functional and Structural Imaging Studies (RRID:SCR_008650) Copy
http://www.montana.edu/massspec/index.html
Provides access to mass spectrometers and mass spectrometry expertise. The facility currently maintains the following equipment Waters Synapt-XS Q-IMS-TOF with Waters I-Class UHPLC; Agilent 6538 Q-TOF with Agilent 1290 UHPLC;Agilent 7800 Inductively Coupled Plasma with Laser Ablation (193 nm);Bruker micrOTOF with Agilent 1290 UHPLC; Agilent 6490 Triple Quadrupole Mass Spectrometer; Bruker MALDI Autoflex; Agilent GC-MS; Waters Synapt G2S-i Q-TOF with Ion Mobility.
Proper citation: Montana State University Mass Spectrometry Core Facility (RRID:SCR_012482) Copy
https://github.com/willtownes/glmpca
Software R package for dimension reduction of non-normally distributed data. Generalized PCA for non-normally distributed data.
Proper citation: glmpca (RRID:SCR_025517) Copy
https://discover.nci.nih.gov/rsconnect/cellminercdb/
Web application integrating cancer cell line pharmacogenomics. Enables exploration and analysis of cancer cell line pharmacogenomic data across different sources. Focuses on cancer patient-derived human cell line molecular and pharmacological data. CellMinerCDB (v1.2) includes several improvements.
Proper citation: CellMinerCDB (RRID:SCR_025649) Copy
https://bioxtas-raw.readthedocs.io/en/latest/
Software tool as GUI based Python program for reduction and analysis of small-angle X-ray solution scattering (SAXS) data.Small-angle scattering data reduction and analysis. Available on Windows, macOS (and OS X), and Linux.
Proper citation: BioXTAS RAW (RRID:SCR_025769) Copy
https://github.com/ay-lab/mustache
Software tool for multi-scale detection of chromatin loops from Hi-C and Micro-C contact maps in high resolutions (10kbp all the way to 500bp and even more). Used to detect chromatin loops caused by interaction of DNA segments with variable size.
Proper citation: Mustache (RRID:SCR_026110) Copy
https://github.com/open2c/cooltools
Software suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Provides suite of computational tools with paired python API and command line access, which facilitates workflows either on high-performance computing clusters or via custom analysis notebooks. As part of the Open2C ecosystem, cooltools also provides detailed introductions to key concepts in Hi-C-data analysis with interactive notebook documentation.
Proper citation: cooltools (RRID:SCR_026118) Copy
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