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https://seer.cancer.gov/lymphomarecode/lymphoma-2020.html
Website describing International Classification of Diseases codes that corresponds to lymphomas in the Surveillance, Epidemiology, and End Results (SEER) registry.
Proper citation: NCI Lymphoid Neoplasm Recode 2020 Revision Definition (RRID:SCR_024686) Copy
Software toolkit to run modern molecular simulations. It can be used either as a standalone application for running simulations, or as a library that enables accelerated calculations for molecular dynamics on high-performance computer architectures.
Proper citation: OpenMM (RRID:SCR_000436) Copy
Center for patient care, education and research on cancer. The institute focuses its research on prevention methods, early detection, treatment and finding cures.
Proper citation: Karmanos Cancer Institute (RRID:SCR_000508) Copy
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
https://github.com/r3fang/SnapATAC
Software package for analyzing scATAC-seq datasets.Used to dissects cellular heterogeneity in unbiased manner and map trajectories of cellular states. Can process data from up to million cells. Incorporates existing tools into comprehensive package for analyzing single cell ATAC-seq dataset.
Proper citation: SnapATAC (RRID:SCR_020981) Copy
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
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
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://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
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
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
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
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
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
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
https://www.sbpdiscovery.org/biomedical-research/shared-resources/cancer-metabolism
Facility that aims to investigate role of metabolism in cancer on cellular and organismal level, combining in vitro and in vivo analysis. Comprehensive metabolic facility, including stable isotope tracing and flux analysis. Provides analysis of metabolism using specialist instruments and methodologies, together with advice on planning experiments and analyzing data. All instruments and approaches are available on fee-for-service basis to Cancer Center scientists, but alsoto outside users. Samples for most services can be shipped, but Seahorse analyzer users need to be local so they can bring live cells for analysis.
Proper citation: Sanford Burnham Prebys Medical Discovery Institute Cancer Metabolism Core Facility (RRID:SCR_014873) Copy
https://sbpdiscovery.org/research/shared-resources/flow-cytometry/
Facility that provides access to high-speed cell sorting, analytical flow cytometry, imaging flow cytometry, and validated immune profiling spectral antibody panels. Core staff provide technical expertise in experiment design, data analysis, hardware and software training, operate the facility cell sorters, and are available to assist with analysis experiments for those who prefer to have their samples run by an expert cytometrist.
Proper citation: Sanford Burnham Prebys Medical Discovery Institute Flow Cytometry Core (RRID:SCR_014854) Copy
http://www.salk.edu/science/core-facilities/integrative-genomics-and-bioinformatics-core/
Core facility established to assist the Salk community with integrating genomics data into their research. The primary focus of the core is to provide analysis support for next-generation sequencing applications.
Proper citation: Salk Institute Razavi Newman Integrative Genomics and Bioinformatics Core Facility (IGC) (RRID:SCR_014842) Copy
Core provides technology for functional proteomics studies and centralized, standardized and quality controlled services locally and globally.
Proper citation: RPPA Core Facility (RRID:SCR_016649) Copy
https://www.mdanderson.org/research/research-resources/core-facilities/proteomics-facility.html
Facility provides mass spectrometry analysis of proteins. Provides access to mass spectrometry based proteomics technologies and services including Protein Identification, Molecular Weight Determination, Quantitative Protein Analysis, Post-translational Modification Analysis, LC or LC-MS Analysis, Equipment Usage, Additional Data Analysis:Bioinformatics, statistics, pathway analysis and Assistance preparing materials for manuscripts or grants.Consultations for custom assays for other MS Services are also available.
Proper citation: University of Texas MD Anderson Cancer Center Proteomics Core Facility (RRID:SCR_017731) Copy
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