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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://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
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
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
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
Collection of revertible protein trap gene-breaking transposon (GBT) insertional mutants in zebrafish with active or cryopreserved lines from initially identified lines. Open to community-wide contributions including expression and functional annotation and represents world-wide central hub for information on how to obtain these lines from diverse members of International Zebrafish Protein Trap Consortium (IZPTC) and integration within other zebrafish community databases including Zebrafish Information Network (ZFIN), Ensembl and National Center for Biotechnology Information. Registration allows users to save their favorite lines for easy access, request lines from Mayo Clinic catalog, contribute to line annotation with appropriate credit, and puts them on optional mailing list for future zfishbook newletters and updates.
Proper citation: zfishbook (RRID:SCR_006896) 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://publications.nigms.nih.gov/insidelifescience/
The NIGMS Inside Life Science series brings you inside the science of health. Each story shows how basic biomedical researchfrom the history of a field to the people doing cutting-edge work todaylays the foundation for advances in disease diagnosis, treatment and prevention. Through explorations of how the body works and highlights from recent studies, you''ll discover even more on what scientists have found and are finding about fundamental life processes. NIGMS supported all of the featured research.
Proper citation: NIGMS Inside Life Science (RRID:SCR_005852) Copy
http://www.sci.utah.edu/cibc/software/231-biomesh3d.html
A free, easy to use program for generating quality meshes for use in biological simulations. It is currently integrated with SCIRun and uses the SCIRun system to visualize the intermediate results. The BioMesh3D program uses a particle system to distribute nodes on the separating surfaces that separate the different materials and then uses the TetGen software package to generate a full tetrahedral mesh.
Proper citation: BioMesh3D (RRID:SCR_009534) Copy
http://amp.pharm.mssm.edu/X2K/
Software tool to produce inferred networks of transcription factors, proteins, and kinases predicted to regulate the expression of the inputted gene list by combining transcription factor enrichment analysis, protein-protein interaction network expansion, with kinase enrichment analysis. It provides the results as tables and interactive vector graphic figures.
Proper citation: eXpression2Kinases (RRID:SCR_016307) Copy
http://compbio.cs.princeton.edu/conservation/
Software for scoring protein sequence conservation using the Jensen-Shannon divergence. It can be used to predict catalytic sites and residues near bound ligands.
Proper citation: Conservation (RRID:SCR_016064) Copy
Interactive Python based interface to Rosetta molecular modeling suite. Stand alone Python based implementation of Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using major Rosetta sampling and scoring functions.
Proper citation: PyRosetta (RRID:SCR_018541) Copy
https://sourceforge.net/projects/saint-apms/files/
Software tool for upgraded implementation of probabilistic scoring of affinity purification mass spectrometry data. Used for filtering high confidence interaction data from affinity purification mass spectrometry experiments. Used for assigning confidence scores to protein-protein interactions based on quantitative proteomics data in AP-MS experiments.
Proper citation: SAINTexpress (RRID:SCR_018562) Copy
https://psbweb05.psb.ugent.be/conet/microbialnetworks/spieceasi.php
Software R package estimates inverse covariance matrix from sequencing data.Statistical method for inference of microbial ecological networks from amplicon sequencing datasets.
Proper citation: Sparse Inverse Covariance Estimation for Ecological Association Inference (RRID:SCR_022646) Copy
https://cran.r-project.org/web/packages/BGLR/
Software R package implements large collection of Bayesian regression models, including parametric variable selection and shrinkage methods and semiparametric procedures.
Proper citation: Bayesian Generalized Linear Regression (RRID:SCR_022522) Copy
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3149502/
Software for comprehensive quantitative measure of splicing impact of complete set of RNA 6-mer sequences by deep sequencing successfully spliced transcripts.
Proper citation: ESRseq score (RRID:SCR_022270) Copy
Software for statistical approach to identify loci within genes that are both significantly enriched in slowly translated codons and evolutionarily conserved, and also co-translational protein folding model.
Proper citation: Coarse grained co-translational folding analysis (RRID:SCR_022271) Copy
https://github.com/rondolab/MR-PRESSO
Software R package for performing Mendelian randomization pleiotropy residual sum and outlier method.Used to identify horizontal pleiotropic outliers in multi instrument summary level MR testing.
Proper citation: MR-PRESSO (RRID:SCR_023697) Copy
Biomedical technology research center that develops and integrates new proteomic technologies for collaborative and service studies, disseminating the new technologies and training scientists in their use.
Proper citation: Proteomics Research Center for Integrative Biology (RRID:SCR_001098) Copy
http://bowtie-bio.sourceforge.net/recount/
RNA-seq gene count datasets built using the raw data from 18 different studies. The raw sequencing data (.fastq files) were processed with Myrna to obtain tables of counts for each gene. For ease of statistical analysis, they combined each count table with sample phenotype data to form an R object of class ExpressionSet. The count tables, ExpressionSets, and phenotype tables are ready to use and freely available. By taking care of several preprocessing steps and combining many datasets into one easily-accessible website, we make finding and analyzing RNA-seq data considerably more straightforward.
Proper citation: ReCount - A multi-experiment resource of analysis-ready RNA-seq gene count datasets (RRID:SCR_001774) Copy
Biomedical technology research center that develops novel cellular imaging technologies, specifically soft X-ray tomography, for visualizing and quantifying the internal structure of whole, hydrated cells, and high-numerical aperture fluorescence microscopy for locating the position of specific cellular molecules. Data from these two imaging modalities can be combined to form a single, correlated imaging view of a cell.
Proper citation: National Center for X-ray Tomography (RRID:SCR_001433) Copy
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