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https://github.com/qiicr/dcmqi

Software library to help with the conversion between imaging research formats and the standard DICOM representation for image analysis results. Used to implement conversion of the data stored in commonly used research formats into the standard DICOM representation. Available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer.

Proper citation: dcmqi (RRID:SCR_016933) 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://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://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

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://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/

Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. An initiative to develop a molecular classification schema that is both clinically and biologically meaningful, based on gene expression and genomic data from tumors (Gliomas) of patients who will be prospectively followed through natural history and treatment phase of their illness. The study will also explore gene expression profiles to determine the responsiveness of the patients and correlate with discrete chromosomal abnormalities. The initiative was designed to obtain a large amount of molecular data on DNA and RNA of freshly collected tumor samples that were collected, processed and analyzed in a standardized fashion to allow for large-scale cross sample analysis. The sample collection is accompanied by careful and prospective clinical data acquisition, allowing a variety of matched molecular and clinical data permitting a wide variety of analyses. GMDI has accrued fresh frozen tumors in the retrospective phase (all from the Henry Ford Hospital, without germline DNA) and fresh frozen tumors in the prospective phase (from a variety of institutions). In addition to characterizing the samples from patients enrolled in GMDI, the microarray group has generated genomic-scale analyses of the many human and canine glioma initiating cells/glioma stem cells (GIC/GSC) lines, as well as many canine and murine normal neural stem cell (NSC) lines produced in laboratory.

Proper citation: Glioma Molecular Dignostic Initiatives (RRID:SCR_003329) Copy   

•   Source: SciCrunch Registry

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

Repository contains PEtab specifications and additional documentation. Data format for specifying parameter estimation problems in systems biology. SBML and TSV based data format for parameter estimation problems in systems biology. Human- and computer- readable format for representing parameter estimation problems in systems biology.

Proper citation: PEtab (RRID:SCR_026915) Copy   

•   Source: SciCrunch Registry

https://github.com/GregorySchwartz/too-many-cells

Software suite of tools, algorithms, and visualizations focusing on relationships between cell clades. This includes new ways of clustering, plotting, choosing differential expression comparisons. Identifies and visualizes relationships of single-cell clades.

Proper citation: TooManyCells (RRID:SCR_025328) Copy   

•   Source: SciCrunch Registry

http://www.phosphosite.org

A freely accessible on-line systems biology resource devoted to all aspects of protein modification, as well as other post-translational modifications. It provides valuable and unique tools for both cell biologists and mass spectroscopists. PhosphoSite is a human- and mouse-centric database. It includes features such as: viewing the locations of modified residues on molecular models; browsing and searching MS2 records by disease, tissue, and cell line; submitting lists of peptides to identify previously reported genes; searching by sub-cellular localization, treatment, tissues, cell types, cell lines and diseases, and protein types and protein domains; searching for experimentally-verified kinase substrates and viewing preferred substrate motifs; and viewing MS2 spectra for peptides and sites not previously published.

Proper citation: PhosphoSitePlus: Protein Modification Site (RRID:SCR_001837) 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

https://seer.cancer.gov/siterecode/icdo3_dwhoheme/index.html

Website describing International Classification of Diseases-Oncology codes that corresponds to different cancer sites in the Surveillance, Epidemiology, and End Results (SEER) registry.

Proper citation: NCI Site Recode ICD-O-3/WHO 2008 Definition (RRID:SCR_024687) 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

http://chtn.nci.nih.gov

The Cancer Diagnosis Program of the National Cancer Institute (NCI) initiated the Cooperative Human Tissue Network (CHTN) in 1987 to provide increased access to human tissue for basic and applied scientists from academia and industry to accelerate the advancement of discoveries in cancer diagnosis and treatment. This unique resource provides remnant human tissues and fluids from routine procedures to investigators who utilize human biospecimens in their research. Unlike tissue banks, the CHTN works prospectively with each investigator to tailor specimen acquisition and processing to meet their specific project requirements. Because the CHTN is funded by the NCI, the CHTN is able to maintain nominal processing fees for its services. The CHTN is comprised of five adult divisions and one pediatric division. Each of the adult divisions coordinates investigator applications/requests based upon the investigator's geographic location within North America. The Pediatric Division manages all investigators who request pediatric specimens only. The CHTN divisions share coordination for requests from outside North America. The CHTN divisions work both independently with individual investigators and together as a seamless unit to fulfill requests that are difficult to serve by any single division. The CHTN's unique informatics system allows each division to effectively communicate and network the needs of its investigators to all CHTN divisions. The Network as a whole can then help fulfill an investigator's request. Biospecimens from surgeries, autopsies and other routine procedures: Malignant, Benign, Diseased, Normal, Biofluids (urine, serum, plasma, buffy coat) High quality specimens at LOW processing fees: Fresh, Frozen, Floating in fixative, RNAlater, Paraffin embedded or and/or unstained slides, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Cooperative Human Tissue Network (RRID:SCR_004446) Copy   

•   Source: SciCrunch Registry

http://cancer.case.edu/sharedresources/tissue/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. The Case Comprehensive Cancer Center''s Biorepository and Tissue Processing Core Facility (BTPC) serves two primary functions: 1. To build an inventory of remnant human tissues, blood and other body fluids (collectively termed biospecimens) targeted towards cancer and other medical research, for later assignment to investigators; and 2. To provide long term, controlled storage of biospecimens for specific researchers. These samples are for research purposes only and may not be used for clinical diagnosis or implantation into humans. Clinical information relating to the samples and donors are collected and maintained in a secure database. Samples and data are de-identified or de-linked before release to the researcher unless he/she has specific IRB approval to gain access to this information. Remnant biospecimens are prospectively collected from surgical procedures, autopsies and clinical laboratories for the BTPC by the Human Tissue Procurement Facility (HTPF), which operates under UH-IRB Protocol 01-02-45. Blood and bone marrow specimens are collected for the BTPC by the Hematopoietic Stem Cell Core Facility (HSCC), which operates under UH-IRB Protocol 09-90-195. The Division of Surgical Pathology at University Hospitals Case Medical Center (UHCMC) has clinical archives of paraffin blocks that can be made available through the BTPC for retrospective research studies under the approval of the Vice Chair for Clinical Affairs at UHCMC. Surgical Pathologists associated with the BTPC are responsible for determining which blocks can be made available and how much material can be removed from the blocks. Types of Tissue Available * Malignant, benign, diseased, normal and normal human tissues * Normal adjacent tissues available paired with tumor specimens in many cases * Tissues are collected from over 50 anatomic sites * Frozen specimens, OCT-embedded and paraffin-embedded tissues * Large array of paraffin-embedded specimens from clinical archives of paraffin blocks and QC research blocks maintained by the HTPF * Peripheral blood and bone marrow samples from initial visits and follow-up procedures are processed to obtain serum and cell fractions for storage * No samples are collected from individuals with known infectious illnesses * Fetal biospecimens are not collected due to state and local statutes

Proper citation: Case Comprehensive Cancer Center Biorepository and Tissue Processing Core Facility (RRID:SCR_004382) Copy   

•   Source: SciCrunch Registry

http://www.uclaaidsinstitute.org/researchareas/clinical_malignancy.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 27, 2012. The National Cancer Institute established centers in the United States and its territories for the collection and distribution of tissues, blood and secretions from patients with clinically-characterized AIDS related malignancies in 1994. The AIDS Malignancy Bank makes these tissues available to qualified investigators in the United States for research on AIDS malignancies. It is hoped that by providing access to these high-quality specimens, research in AIDS-related malignancies will be encouraged and expanded. The AMB contains formalin-fixed paraffin-embedded tissues, fresh-frozen tissues, malignant-cell suspensions, fine-needle aspirates, and cell lines from AIDS-related malignancies. The bank also contains serum, plasma, urine, bone marrow, cervical secretions, anal swabs, saliva semen and multi-site autopsy tissues from patients with AIDS-related malignancies who have participated in clinical trials. The bank has an associated database that contains prognostic, staging, outcome and treatment data on patients from whom tissues were obtained. Researchers pay for preparation and shipping of specimens.

Proper citation: AIDS Malignancy Bank (RRID:SCR_004417) Copy   

•   Source: SciCrunch Registry

https://htrn.osu.edu/Services/Biorepository/Pages/default.aspx

The HTRN biospecimen bank is comprised of samples for the Ohio State University Cancer and Leukemia Group B Pathology Coordinating Office (CALGB-PCO) and the Ohio State University Midwestern Division of the Cooperative Human Tissue Network (CHTN). The CALGB-PCO banks biospecimens donated by patients enrolled in clinical trials. Samples can include tumor and normal tissue, plasma, serum, whole blood and white blood cells and urine. All of these samples are used later in correlative studies. The Midwestern Division of the CHTN stores a temporary biospecimen bank of tumor and normal tissue, tissue slides and paraffin embedded tissue blocks for research investigators throughout the country and Canada who are trying to find a cure for cancer. As part of the HTRN biospecimen bank, a Rees Scientific equipment monitoring system helps to secure the integrity and quality of samples stored in the biorepository. Scientific research within the HTRN is currently underway to determine the best methods in tissue storage for long term use. The NCI First-Generation Guidelines for NCI-Supported Biorepositories and the NCI Best Practices for Biospecimen Resources are continuously reviewed and adapted by the HTRN.

Proper citation: Ohio State Biorepository (RRID:SCR_004714) Copy   

•   Source: SciCrunch Registry

http://pilgrm.princeton.edu

PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.

Proper citation: PILGRM (RRID:SCR_004749) Copy   

•   Source: SciCrunch Registry