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http://discover.nci.nih.gov/gominer/

GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.

Proper citation: GoMiner (RRID:SCR_002360) Copy   

•   Source: SciCrunch Registry

http://dctd.cancer.gov/

Division of NCI that takes prospective cancer detection and treatment leads, facilitates their paths to clinical application, and expedites the initial and subsequent large-scale testing of new agents, biomarkers, imaging tests, and other therapeutic interventions (radiation, surgery, immunotherapy) in patients. DCTD, like all of NCI, supports many programs that could not be done without government funding - investigators supported by the division engage in scientifically sound, high-risk research that may yield great benefits for patients with cancer, but are too difficult or risky for industry or academia to pursue. This includes a particular emphasis on the development of distinct molecular signatures for cancer, refined molecular assays, and state-of-the-art imaging techniques that will guide oncologic therapy in the future. The division has eight major programs that work together to bring unique molecules, diagnostic tests, and therapeutic interventions from the laboratory bench to the patient bedside: * Cancer Diagnosis Program * Cancer Imaging Program * Cancer Therapy Evaluation Program * Developmental Therapeutics Program * Radiation Research Program * Translational Research Program * Biometrics Research Branch * Office of Cancer Complementary and Alternative Medicine

Proper citation: DCTD (RRID:SCR_004196) Copy   

•   Source: SciCrunch Registry

https://www.robotreviewer.net/about

Open source web based system that uses machine learning and NLP to semi automate biomedical evidence synthesis, to aid practice of Evidence Based Medicine. Processes full text journal articles describing randomized controlled trials. Designed to automatically extract key data items from reports of clinical trials.

Proper citation: RobotReviewer (RRID:SCR_021064) Copy   

•   Source: SciCrunch Registry

https://www.synapse.org/#!Synapse:syn22345748/wiki/605339

Reference dataset of multiplexed immunofluorescence microscopy images collected at HMS Laboratory of Systems Pharmacology. Includes set of images of different types for development and benchmarking of computational methods for image processing. As of 4/2/2021, EMIT comprises tissue microarray containing cores from 34 cancer, non-neoplastic diseases, and normal tissue collected from clinical discards under IRB supervised protocol. TMA was imaged using cyclic immunofluorescence method. Additional extensions of EMIT are currently in the planning stages. Long term goal is to compose ImageNet like resource for highly multiplexed images of tissues and tumors by consolidating high quality curated datasets.

Proper citation: Exemplar Microscopy Images of Tissues (RRID:SCR_021052) 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://github.com/abyzovlab/CNVpytor

Software Python package and command line tool for CNV/CNA analysis from depth of coverage by mapped reads. Software tool for CNV/CNA detection and analysis from read depth and allele imbalance in whole genome sequencing.

Proper citation: CNVpytor (RRID:SCR_021627) Copy   

•   Source: SciCrunch Registry

https://cumulus.readthedocs.io/en/stable

Software tool as cloud based single cell genomics and spatial transcriptomics data analysis framework that is scalable to massive amounts of data and able to process variety of data types. Consists of cloud analysis workflow, Python analysis package and visualization application. Supports analysis of single-cell RNA-seq, CITE-seq, Perturb-seq, single-cell ATAC-seq, single-cell immune repertoire and spatial transcriptomics data.

Proper citation: Cumulus (RRID:SCR_021644) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org

International database for laboratory mouse. Data offered by The Jackson Laboratory includes information on integrated genetic, genomic, and biological data. MGI creates and maintains integrated representation of mouse genetic, genomic, expression, and phenotype data and develops reference data set and consensus data views, synthesizes comparative genomic data between mouse and other mammals, maintains set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides technical support for database users. Projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.

Proper citation: Mouse Genome Informatics (MGI) (RRID:SCR_006460) Copy   

•   Source: SciCrunch Registry

http://www.mc.vanderbilt.edu/root/vumc.php?site=chtn%20western%20division

The Cooperative Human Tissue Network- Western Division at Vanderbilt University Medical Center is one of six institutions throughout the country funded by the National Cancer Institutes to procure and distribute remnant human tissues to biomedical researchers throughout the United States and Canada. CHTN operates through a shared networking system which allows investigators greater access to available research specimens. CHTN offers a variety of preparation and preservation techniques to ensure investigators are receiving the quality specimens needed for research. Remnant tissues are obtained from surgical resections and autopsies and are procured to the specifications of the investigator.

Proper citation: Cooperative Human Tissue Network Western Division at Vanderbilt University Medical Center (RRID:SCR_006661) Copy   

•   Source: SciCrunch Registry

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry

https://github.com/broadinstitute/ichorCNA

Software tool that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. Used to simultaneously segment genome, predict large scale copy number alterations, and estimate tumor fraction of ultra low pass whole genome sequencing sample.

Proper citation: ichorCNA (RRID:SCR_024768) 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

https://www.npatlas.org

Open access knowledge base for microbial natural products discovery. Database of microbially derived natural product structures. Provides coverage of bacterial and fungal natural products to visualize chemical diversity. Includes compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. Interactive web portal permits searching by structure, substructure, and physical properties. Provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. Atlas has been developed under FAIR principles.

Proper citation: Natural Products Atlas (RRID:SCR_025107) Copy   

•   Source: SciCrunch Registry

https://github.com/PhysiCell-Tools/PhysiCell-Studio

Software graphical tool to allow easy editing of (XML) model, create initial positions of cells, run simulation, and visualize results. To contribute, fork and make PRs to the development branch. Used to create, execute, and visualize multicellular model using PhysiCell.

Proper citation: PhysiCell Studio (RRID:SCR_025311) Copy   

•   Source: SciCrunch Registry

https://pvactools.readthedocs.io/en/latest/

Software toolkit to identify and visualize cancer neoantigens. Cancer immunotherapy tools suite consisting of following tools: pVACseq as cancer immunotherapy pipeline for identifying and prioritizing neoantigens from VCF file; pVACbind as cancer immunotherapy pipeline for identifying and prioritizing neoantigens from FASTA file; pVACfuse as tool for detecting neoantigens resulting from gene fusions; pVACvector as tool designed to aid specifically in construction of DNA-based cancer vaccines; pVACview as application based on R Shiny that assists users in reviewing, exploring and prioritizing neoantigens from results of pVACtools processes for personalized cancer vaccine design.

Proper citation: pVACtools (RRID:SCR_025435) Copy   

•   Source: SciCrunch Registry

http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/

Software tool for ultra fast eQTL analysis via large matrix operations.

Proper citation: MatrixEQTL (RRID:SCR_025513) Copy   

•   Source: SciCrunch Registry

https://github.com/phillipnicol/scGBM

Software application for model-based dimensionality reduction of scRNA-seq data. Quantifies uncertainty in each cell's latent position and leverages these uncertainties to assess confidence associated with given cell clustering. On real and simulated single-cell data produces low-dimensional embeddings that better capture relevant biological information while removing unwanted variation. Used for model-based dimensionality reduction for single-cell RNA-seq with generalized bilinear models.

Proper citation: scGBM (RRID:SCR_025518) Copy   

•   Source: SciCrunch Registry

https://github.com/ccipd/MRQy

Software quality assurance and checking tool for quantitative assessment of magnetic resonance imaging and computed tomography data. Used for quality control of MR imaging data.

Proper citation: MRQy (RRID:SCR_025779) Copy   

•   Source: SciCrunch Registry

https://github.com/STAR-Fusion/STAR-Fusion

Software tool to leverage chimeric and discordant read alignments identified by STAR aligner to predict fusions. Component of Trinity Cancer Transcriptome Analysis Toolkit. Used to identify candidate fusion transcripts supported by Illumina reads. Maps junction reads and spanning reads to reference annotation set.

Proper citation: STAR-Fusion (RRID:SCR_025853) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/methylSig.html

Software R package as whole genome DNA methylation analysis pipeline. Used for testing differentially methylated cytosines or regions in whole-genome bisulfite sequencing or reduced representation bisulfite sequencing experiments. Several options exist for either site-specific or sliding window tests, and variance estimation.

Proper citation: MethylSig (RRID:SCR_025849) Copy   

•   Source: SciCrunch Registry