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https://skyline.gs.washington.edu/labkey/project/home/software/Skyline/begin.view

Software tool as Windows client application for targeted proteomics method creation and quantitative data analysis. Open source document editor for creating and analyzing targeted proteomics experiments. Used for large scale quantitative mass spectrometry studies in life sciences.

Proper citation: Skyline (RRID:SCR_014080) Copy   

•   Source: SciCrunch Registry

http://www.cse-lab.ethz.ch/index.php?&option=com_content&view=article&id=363

Software tool for automated analysis of monolayer wound healing assays. Available as a stand alone application for Macintosh and Windows and as a source code. Offers a graphical user interface for inspection of analysis results and manual modification of analysis parameters., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Tscratch (RRID:SCR_014282) Copy   

•   Source: SciCrunch Registry

http://www.pathwaycommons.org/

Data management software that runs the Pathway Commons web service. It makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Main features: * Import pipeline capable of aggregating pathway and interaction data sets from multiple sources, including: MINT, IntAct, HPRD, DIP, BioCyc, KEGG, PUMA2 and Reactome. * Import/Export support for the Proteomics Standards Initiative Molecular Interaction (PSI-MI) and the Biological Pathways Exchange (BioPAX) XML formats. * Data visualization and analysis via Cytoscape. * Simple HTTP URL based XML web service. * Complete software is freely available for local install. Easy to install and administer. * Partly funded by the U.S. National Cancer Institute, via the Cancer Biomedical Informatics Grid (caBIG) and aims to meet silver-level requirements for software interoperability and data exchange.

Proper citation: cPath (RRID:SCR_001749) Copy   

•   Source: SciCrunch Registry

https://david.ncifcrf.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

Proper citation: DAVID (RRID:SCR_001881) Copy   

•   Source: SciCrunch Registry

http://pslid.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

Annotated database of fluorescence microscope images depicting subcellular location proteins with two interfaces: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. The annotations in PSLID provide a description of sample preparation and fluorescence microscope imaging.

Proper citation: Protein Subcellular Location Image Database (RRID:SCR_008663) Copy   

•   Source: SciCrunch Registry

http://www.cancerimagingarchive.net/

Archive of medical images of cancer accessible for public download. All images are stored in DICOM file format and organized as Collections, typically patients related by common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. Neuroimaging data sets include clinical outcomes, pathology, and genomics in addition to DICOM images. Submitting Data Proposals are welcomed.

Proper citation: Cancer Imaging Archive (TCIA) (RRID:SCR_008927) Copy   

•   Source: SciCrunch Registry

http://akt.ucsf.edu/EGAN/

Exploratory Gene Association Networks (EGAN) is a software tool that allows a bench biologist to visualize and interpret the results of high-throughput exploratory assays in an interactive hypergraph of genes, relationships (protein-protein interactions, literature co-occurrence, etc.) and meta-data (annotation, signaling pathways, etc.). EGAN provides comprehensive, automated calculation of meta-data coincidence (over-representation, enrichment) for user- and assay-defined gene lists, and provides direct links to web resources and literature (NCBI Entrez Gene, PubMed, KEGG, Gene Ontology, iHOP, Google, etc.). EGAN functions as a module for exploratory investigation of analysis results from multiple high-throughput assay technologies, including but not limited to: * Transcriptomics via expression microarrays or RNA-Seq * Genomics via SNP GWAS or array CGH * Proteomics via MS/MS peptide identifications * Epigenomics via DNA methylation, ChIP-on-Chip or ChIP-Seq * In-silico analysis of sequences or literature EGAN has been built using Cytoscape libraries for graph visualization and layout, and is comparable to DAVID, GSEA, Ingenuity IPA and Ariadne Pathway Studio. There are pre-collated EGAN networks available for human (Homo sapiens), mouse (Mus musculus), rat (Rattus norvegicus), chicken (Gallus gallus), zebrafish (Danio rerio), fruit fly (Drosophila melanogaster), nematode (Caenorhabditis elegans), mouse-ear cress (Arabidopsis thaliana), rice (Oryza sativa) and brewer's yeast (Saccharomyces cerevisiae). There is now an EGAN module available for GenePattern (human-only). Platform: Windows compatible, Mac OS X compatible, Linux compatible

Proper citation: EGAN: Exploratory Gene Association Networks (RRID:SCR_008856) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/sites/GeneTests/lab

The GeneTests Web site, a publicly funded medical genetics information resource developed for physicians, other healthcare providers, and researchers, is available at no cost to all interested persons. By providing current, authoritative information on genetic testing and its use in diagnosis, management, and genetic counseling, GeneTests promotes the appropriate use of genetic services in patient care and personal decision making. At This Site: * GeneReviews: Expert-authored peer-reviewed disease descriptions * Laboratory Directory: International directory of genetic testing laboratories * Clinic Directory: International directory of genetics and prenatal diagnosis clinics * Educational Materials: Illustrated glossary, information on genetic services, PowerPoint presentations, annotated Internet resources We comply with the HONcode standard for trustworthy health information.

Proper citation: GeneTests (RRID:SCR_010725) Copy   

•   Source: SciCrunch Registry

http://proteogenomics.musc.edu/ma/musc_madb.php?page=home&act=manage

Database that is a repository for DNA microarray data generated by MUSC investigators as well as researchers in the global research community.

Proper citation: MUSC DNA Microarray Database (RRID:SCR_010977) Copy   

•   Source: SciCrunch Registry

https://ibeximagingcommunity.github.io/ibex_imaging_knowledge_base/

Open, global repository as central resource for reagents, protocols, panels, publications, software, and datasets. In addition to IBEX, we support standard, single cycle multiplexed imaging (Multiplexed 2D imaging), volume imaging of cleared tissues with clearing enhanced 3D (Ce3D), highly multiplexed 3D imaging (Ce3D-IBEX), and extension of the IBEX dye inactivation protocol to the Leica Cell DIVE (Cell DIVE-IBEX). Committed to sharing knowledge related to multiplexed imaging. Antibody validation community knowledgebase.

Proper citation: IBEX Knowledge Base (RRID:SCR_025296) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. REMBRANDT is a data repository containing diverse types of molecular research and clinical trials data related to brain cancers, including gliomas, along with a wide variety of web-based analysis tools that readily facilitate the understanding of critical correlations among the different data types. REMBRANDT aims to be the access portal for a national molecular, genetic, and clinical database of several thousand primary brain tumors that is fully open and accessible to all investigators (including intramural and extramural researchers), as well as the public at-large. The main focus is to molecularly characterize a large number of adult and pediatric primary brain tumors and to correlate those data with extensive retrospective and prospective clinical data. Specific data types hosted here are gene expression profiles, real time PCR assays, CGH and SNP array information, sequencing data, tissue array results and images, proteomic profiles, and patients'''' response to various treatments. Clinical trials'''' information and protocols are also accessible. The data can be downloaded as raw files containing all the information gathered through the primary experiments or can be mined using the informatics support provided. This comprehensive brain tumor data portal will allow for easy ad hoc querying across multiple domains, thus allowing physician-scientists to make the right decisions during patient treatments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Repository of molecular brain neoplasia data (RRID:SCR_004704) Copy   

•   Source: SciCrunch Registry

http://smd.princeton.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 17, 2021. Database to store, annotate, view, analyze and share microarray data. It provides registered users access to their own data, provides users access to public data, and tools with which to analyze those data, to any public user anywhere in the world. The GenePattern software package has been incorporated directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability. SMD search options allow the user to Search By Experiments, Search By Datasets, or Search By Gene Names. Web services are provided using common standards, such as Simple Object Access Protocol (SOAP). This enables both local and remote researchers to connect to an installation of the database and retrieve data using pre-defined methods, without needing to resort to use of a web browser.

Proper citation: SMD (RRID:SCR_004987) Copy   

•   Source: SciCrunch Registry

http://www.webarraydb.org/webarray/index.html

An open source integrated microarray database and analysis suite that features convenient uploading of data for storage in a MIAME (Minimal Information about a Microarray Experiment) compliant fashion. It allows data to be mined with a large variety of R-based tools, including data analysis across multiple platforms. Different methods for probe alignment, normalization and statistical analysis are included to account for systematic bias. Student's t-test, moderated t-tests, non-parametric tests and analysis of variance or covariance (ANOVA/ANCOVA) are among the choices of algorithms for differential analysis of data. Users also have the flexibility to define new factors and create new analysis models to fit complex experimental designs. All data can be queried or browsed through a web browser. The computations can be performed in parallel on symmetric multiprocessing (SMP) systems or Linux clusters.

Proper citation: WebArrayDB (RRID:SCR_005577) Copy   

•   Source: SciCrunch Registry

http://edwardslab.bmcb.georgetown.edu/ws/peptideMapper/

The PeptideMapper Web-Service provides alignments of peptide sequence alignments to proteins, mRNA, EST, and HTC sequences from Genbank, RefSeq, UniProt, IPI, VEGA, EMBL, and HInvDb. This mapping infrastructure is supported, in part, by the compressed peptide sequence database infrastructure (Edwards, 2007) which enables a fast, suffix-tree based mapping of peptide sequences to gene identifiers and a gene-focused detailed mapping of peptide sequences to source sequence evidence. The PeptideMapper Web-Service can be used interactively or as a web-service using either HTTP or SOAP requests. Results of HTTP requests can be returned in a variety of formats, including XML, JSON, CSV, TSV, or XLS, and in some cases, GFF or BED; results of SOAP requests are returned as SOAP responses. The PeptideMapper Web-Service maps at most 20 peptides with length between 5 and 30 amino-acids in each request. The number of alignments returned, per peptide, gene, and sequence type, is set to 10 by default. The default can be changed on the interactive alignments search form or by using the max web-service parameter.

Proper citation: PeptideMapper (RRID:SCR_005763) Copy   

•   Source: SciCrunch Registry

http://www.chemnavigator.com/cnc/services/SCSORS_Overview.asp

ChemNavigator has extended its agreement with NCI to include the development of a new Semi-Custom Synthesis On-line Request System (SCSORS), funded mostly by NCI with additional financial support from the NIH Chemical Genomics Center (NCGC). The new SCSORS project will provide the NIH access to the world''s supply of synthetic chemistry available for drug discovery. Once fully formed, SCSORS will provide a strategy for all NIH scientists to circulate requests for specific chemical samples among thousands, if not tens of thousands, of synthetic chemists at suppliers registered in the system. Sample quantities will range from milligram up to kilogram scale requests. Suppliers will be provided tools that allow them to review these requests and make proposals to NIH scientists for the synthesis of substances. It is expected that using the SCSORS strategy will allow the NIH to acquire chemical samples at less than 10% of the internal cost of synthesis while offering access to world wide chemical expertise and diversity. Once fully implemented, SCSORS will become an archive of commercially accessible custom chemistry products for pharmaceutical research. It is expected that this database of commercially accessible substances will grow to over 250 million substances in the coming two years.

Proper citation: SCSORS - Semi-Custom Synthesis On-line Request System (RRID:SCR_005636) Copy   

•   Source: SciCrunch Registry

http://cgap.nci.nih.gov/Genes/GOBrowser

With the CGAP GO browser, you can browse through the GO vocabularies, and find human and mouse genes assigned to each term. GO data updated every few months. Platform: Online tool

Proper citation: CGAP GO Browser (RRID:SCR_005676) Copy   

•   Source: SciCrunch Registry

https://seahorse.networkmedicine.org

Web-based database and search tool for exploratory data analysis in which we have pre-computed statistical associations between available data elements. Large-scale, open-access data sets such as the Genotype Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA) include multi-omic data on large numbers of samples along with extensive clinical and phenotypic information. Allows users to explore significant associations using tabulated summary statistics, data visualizations, and functional enrichment analyses (using RNA-seq data) for identified sets of genes.

Proper citation: SEAHORSE (RRID:SCR_027399) Copy   

•   Source: SciCrunch Registry

http://www.nihpromis.org/

Repository of person centered measures that evaluates and monitors physical, mental, and social health in adults and children.

Proper citation: Patient-Reported Outcomes Measurement Information System (RRID:SCR_004718) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://cabig.cancer.gov

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 19, 2016. It has been integrated into the National Cancer Informatics Program (NCIP). The National Cancer Institute launched the cancer Biomedical Informatics Grid (caBIG) to create a virtual network of interconnected data, individuals, and organizations that worked together to redefine how cancer research is conducted. caBIG capabilities allowed researchers and clinicians to collaborate more effectively so that complex research questions might be asked and answered faster and more effectively. The mission of caBIG was to develop a truly collaborative information network that accelerated the discovery of new approaches for the detection, diagnosis, treatment, and prevention of cancer, ultimately improving patient outcomes.

Proper citation: Cancer Biomedical Informatics Grid (RRID:SCR_003328) Copy   

•   Source: SciCrunch Registry