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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://discover.nci.nih.gov/gominer/GoCommandWebInterface.jsp
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A web program that organizes lists of genes of interest (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology and automates the analysis of multiple microarrays then integrates the results across all of them in exportable output files and visualizations. High-Throughput GoMiner is an enhancement of GoMiner and is implemented with both a command line interface and a web interface. The program can also: efficiently perform automated batch processing of an arbitrary number of microarrays; produce a human- or computer-readable report that rank-orders the multiple microarray results according to the number of significant GO categories; integrate the multiple microarray results by providing organized, global clustered image map visualizations of the relationships of significant GO categories; provide a fast form of false discovery rate multiple comparisons calculation; and provide annotations and visualizations for relating transcription factor binding sites to genes and GO categories.
Proper citation: High-Throughput GoMiner (RRID:SCR_000173) Copy
http://www.cancerdiagnosis.nci.nih.gov/
National program to improve the diagnosis and assessment of cancer by moving scientific knowledge into clinical practice by coordinating and funding resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens. The Cancer Diagnosis Program is divided into four branches: Biorepository and Biospecimen Research Branch (BBRB), Diagnostic Biomarkers and Technology Branch (DBTB), Diagnostics Evaluation Branch (DEB), and the Pathology Investigation and Resources Branch (PIRB).
Proper citation: CDP (RRID:SCR_004236) Copy
http://cancer.osu.edu/Pages/index.aspx
As the Midwest''s first and Ohio''s only fully dedicated cancer hospital and research institute, The Ohio State University Comprehensive Cancer CenterArthur G. James Cancer Hospital and Solove Research Institute (OSUCCC-James) is one of the nation''s premier cancer centers for the prevention, detection and treatment of cancer. The OSUCCC-James is one of only 40 centers in the United States designated by the National Cancer Institute a Comprehensive Cancer Center. In addition, the OSUCCC-James is a founding member of the National Comprehensive Cancer Network (NCCN), an alliance of 21 of the world''s leading cancer centers that develops clinical practice guidelines to improve the quality and effectiveness of care provided to patients with cancer. The Ohio State cancer program is part of The Ohio State University, the largest public university in the nation. We are affiliated with The Ohio State University Medical Center, one of the largest and most diverse academic medical centers in the nation and the only academic medical center in central Ohio. The cancer program at Ohio State encompasses more than 200 comprehensive cancer center members from 13 of the 18 colleges at The Ohio State University and includes physicians from 16 specialties. The OSUCCCJames'' singular focus on cancer has led to multiple accomplishments that have changed the standards of care with respect to prevention, diagnosis and treatment, in a way that substantially improves outcomes for cancer patients.
Proper citation: OSUCCC-James (RRID:SCR_004790) Copy
http://www.xiphophorus.txstate.edu/
Supplier of xiphophorus (platyfish or swordtails) from pedigreed parental lines, representing variety of species. In addition to supplying strains and providing consultation on husbandry and genetic questions, the XGSC produces custom interspecies hybrids (both first generation F1, and backcross hybrid generation BC1) for a variety of projects.
Proper citation: Xiphophorus Genetic Stock Center (RRID:SCR_008340) Copy
An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).
Proper citation: iTools (RRID:SCR_009626) Copy
Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.
Proper citation: HOMER (RRID:SCR_010881) Copy
Database of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.
Proper citation: GeneSigDB (RRID:SCR_013275) 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://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.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/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
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
https://github.com/vlink/marge
Software package that integrates genome wide genetic variation with epigenetic data to identify collaborative transcription factor pairs. Optimized to work with chromatin accessibility assays such as ATAC-seq or DNase I hypersensitivity, as well as transcription factor binding data collected by ChIP-seq. Used to identify combinations of cell type specific transcription factors while simultaneously interpreting functional effects of non-coding genetic variation.
Proper citation: Motif Mutation Analysis for Regulatory Genomic Elements (RRID:SCR_021902) Copy
https://github.com/kukionfr/VAMPIRE_open
Software tool for analysis of cell and nuclear morphology from fluorescence or bright field images. Enables profiling and classification of cells into shape modes based on equidistant points along cell and nuclear contours. Robust method to quantify cell morphological heterogeneity.
Proper citation: VAMPIRE (RRID:SCR_021721) Copy
Web platform for downstream analysis and visualization of proteomics data. Server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. Primary input for server consists of set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values.
Proper citation: piNET (RRID:SCR_018693) Copy
https://cistrome.shinyapps.io/timer/
Web server for comprehensive analysis of tumor infiltrating immune cells. Web tool for systematical analysis of immune infiltrates across diverse cancer types. Allows users to input function specific parameters, with resulting figures dynamically displayed to access tumor immunological, clinical, and genomic features.
Proper citation: TIMER (RRID:SCR_018737) Copy
Web service for querying or retrieving gene annotation data.
Proper citation: MyGene.info (RRID:SCR_018660) Copy
https://rosie.graylab.jhu.edu/docking2
Unified web framework for Rosetta applications. Web interface for selected Rosetta protocols. Web front end for Rosetta software suite. Provides common user interface for Rosetta protocols, stable application programming interface for developers to add additional protocols, flexible back-end to allow leveraging of computer cluster resources shared by Rosetta Commons member institutions, and centralized administration by Rosetta Commons to ensure continuous maintenance. Offers general and speedy paradigm for serverification of Rosetta applications. Lowers barriers to Rosetta use for broader biological community.
Proper citation: ROSIE (RRID:SCR_018764) Copy
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