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https://www.signalingpathways.org/ominer/query.jsf

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on February 25, 2022.Software tool as knowledge environment resource that accrues, develops, and communicates information that advances understanding of structure, function, and role in disease of nuclear receptors (NRs) and coregulators. It specifically seeks to elucidate roles played by NRs and coregulators in metabolism and development of metabolic disorders. Includes large validated data sets, access to reagents, new findings, library of annotated prior publications in field, and journal covering reviews and techniques.As of March 20, 2020, NURSA is succeeded by the Signaling Pathways Project (SPP).

Proper citation: Nuclear Receptor Signaling Atlas (RRID:SCR_003287) Copy   

•   Source: SciCrunch Registry

https://github.com/EpistasisLab/ReBATE

Open source software Python package to compare relief based feature selection algorithms used in data mining. Used for feature selection in any bioinformatics problem with potentially predictive features and target outcome variable, to detect feature interactions without examination of all feature combinations, to detect features involved in heterogeneous patterns of association such as genetic heterogeneity .

Proper citation: ReBATE (RRID:SCR_017139) Copy   

•   Source: SciCrunch Registry

https://www.accordtrial.org/public

Study testing whether strict glucose control lowers the risk of heart disease and stroke in adults with type 2 diabetes. In addition the study is exploring: 1) Whether in the context of good glycemic control the use of different lowering lipid drugs will further improve these outcomes and 2) If strict control of blood pressure will also have additional beneficial effects on reducing cardiovascular disease. The design was a randomized, multicenter, double 2 X 2 factorial trial in 10,251 patients with type 2 diabetes mellitus. It was designed to test the effects on major CVD events of intensive glycemia control, of fibrate treatment to increase HDL-cholesterol and lower triglycerides (in the context of good LDL-C and glycemia control), and of intensive blood pressure control (in the context of good glycemia control), each compared to an appropriate control. All 10,251 participants were in an overarching glycemia trial. In addition, one 2 X 2 trial addressed the lipid question in 5,518 of the participants and the other 2 X 2 trial addressed the blood pressure question in 4,733 of the participants. The glycemia trial was terminated early due to higher mortality in the intensive compared with the standard glycemia treatment strategies. The results were published in June 2008 (N Eng J Med 2008;358:2545-59). Study-delivered treatment for all ACCORD participants was stopped on June 30, 2009, and the participants were assisted as needed in transferring their care to a personal physician. The lipid and blood pressure results (as well as the microvascular outcomes and eye substudy results) were published in 2010. All participants are continuing to be followed in a non-treatment observational study.

Proper citation: ACCORD (RRID:SCR_009015) Copy   

•   Source: SciCrunch Registry

https://github.com/aametwally/Metabolic_Subphenotype_Predictor

Software repository contains code for Inference of T2D metabolic subphenotypes (MuscleIR, Beta-cell Function, Incretin Effect, Hepatic IR), Identification of dominant metabolic subphenotype, Feature extraction from glucose tiemseries, Extraction of reduced representation of glucose tiemseries,Visualization of metabolic phenotypes based on various glucose-related metrics,Concordance between CGM and Venous glucose values from at home and at clinical setting, Classification of metabolic subphenotypes.

Proper citation: Metabolic Subphenotype Predictor (RRID:SCR_027192) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/cardiovascularproteomics/

The Cardiovascular Proteomics Center is a research center funded by the NIH/NHLBI to analyze and identify proteins that may be modified or created by oxidative stress. The CPC is developing and applying new proteomics methodology and instrumentation to the analysis of known proteins and those yet to be discovered.

Proper citation: Cardiovascular Proteomics Center (RRID:SCR_000603) Copy   

•   Source: SciCrunch Registry

https://medicine.yale.edu/keck/nida/yped/

Open source system for storage, retrieval, and integrated analysis of large amounts of data from high throughput proteomic technologies. YPED currently handles LCMS, MudPIT, ICAT, iTRAQ, SILAC, 2D Gel and DIGE. The repository contains data sets which have been released for public viewing and downloading by the responsible Primary Investigators. It includes proteomic data generated by the Yale NIDA Neuroproteomics Center (http://medicine.yale.edu/keck/nida/index.aspx). Sample descriptions are compatible with the evolving MIAPE standards.

Proper citation: YPED (RRID:SCR_001436) Copy   

•   Source: SciCrunch Registry

http://www.macaque.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on June 8, 2020.Macaque genomic and proteomic resources and how they are providing important new dimensions to research using macaque models of infectious disease. The research encompasses a number of viruses that pose global threats to human health, including influenza, HIV, and SARS-associated coronavirus. By combining macaque infection models with gene expression and protein abundance profiling, they are uncovering exciting new insights into the multitude of molecular and cellular events that occur in response to virus infection. A better understanding of these events may provide the basis for innovative antiviral therapies and improvements to vaccine development strategies.

Proper citation: Macaque.org (RRID:SCR_002767) Copy   

•   Source: SciCrunch Registry

http://www.tarp.nih.gov/

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   

•   Source: SciCrunch Registry

https://github.com/caleblareau/mgatk

Software python-based command line interface for processing .bam files with mitochondrial reads and generating high-quality heteroplasmy estimation from sequencing data. This package places a special emphasis on mitochondrial genotypes generated from single-cell genomics data, primarily mtscATAC-seq, but is generally applicable across other assays.

Proper citation: mgatk (RRID:SCR_021159) Copy   

•   Source: SciCrunch Registry

https://github.com/humanlongevity/HLA

Software tool for fast and accurate HLA typing from short read sequence data. Iteratively refines mapping results at amino acid level to achieve four digit typing accuracy for both class I and II HLA genes, taking only 3 min to process 30× whole genome BAM file on desktop computer.

Proper citation: xHLA (RRID:SCR_022277) Copy   

•   Source: SciCrunch Registry

https://lincsportal.ccs.miami.edu/signatures/home

Primary access point for compendium of LINCS data with substantial changes in data architecture and APIs, completely redesigned user interface, and enhanced curated metadata annotations to support more advanced, intuitive and deeper querying, exploration and analysis capabilities. LINCS datasets are accessible at data point level enabling users to directly access and download any subset of signatures across entire library independent from originating source, project or assay. Newly designed query interface enables global metadata search with autosuggest across all annotations associated with perturbations, model systems, and signatures.

Proper citation: LINCS Data Portal 2.0 (RRID:SCR_022566) Copy   

•   Source: SciCrunch Registry

http://www.nhlbi.nih.gov/guidelines/obesity/BMI/bmicalc.htm

Body Mass Index (BMI) for adults can be calculated using only height and weight. Body mass index (BMI) is a measure of body fat based on height and weight that applies to adult men and women.

Proper citation: Body Mass Index Calculator (RRID:SCR_000122) Copy   

•   Source: SciCrunch Registry

http://proteomics.ucsd.edu/Software/NeuroPedia/index.html

A neuropeptide encyclopedia of peptide sequences (including genomic and taxonomic information) and spectral libraries of identified MS/MS spectra of homolog neuropeptides from multiple species.

Proper citation: NeuroPedia (RRID:SCR_001551) Copy   

•   Source: SciCrunch Registry

https://maayanlab.cloud/X2K

Web service to predict involvement of upstream cell signaling pathways, given signature of differentially expressed genes. Used to linking expression signatures to upstream cell signaling networks.

Proper citation: X2K Web (RRID:SCR_023624) Copy   

•   Source: SciCrunch Registry

https://pmc.ncbi.nlm.nih.gov/articles/PMC4525701/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 25,2025. Web tool to parse Sanger sequencing chromatograms with double peaks into wildtype and alternative allele sequences. Used to separate chromatogram data containing ambiguous base calls into wildtype and mutant allele sequences.Used for identification of unknown indels using sanger sequencing of polymerase chain reaction products.

Proper citation: Poly Peak Parser (RRID:SCR_023776) Copy   

•   Source: SciCrunch Registry

http://interactome.baderlab.org/

Project portal for the Human Reference Protein Interactome Project, which aims generate a first reference map of the human protein-protein interactome network by identifying binary protein-protein interactions (PPIs). It achieves this by systematically interrogating all pairwise combinations of predicted human protein-coding genes using proteome-scale technologies.

Proper citation: Human Reference Protein Interactome Project (RRID:SCR_015670) Copy   

•   Source: SciCrunch Registry

https://software.broadinstitute.org/cancer/cga/polysolver

Software tool for HLA typing based on whole exome sequencing data and infers alleles for three major MHC class I genes. Enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using inferred alleles as reference.

Proper citation: Polysolver (RRID:SCR_022278) Copy   

•   Source: SciCrunch Registry

https://maayanlab.cloud/sigcom-lincs

Web server that serves over million gene expression signatures processed, analyzed, and visualized from LINCS, GTEx, and GEO. Data and metadata search engine for gene expression signatures.

Proper citation: SigCom LINCS (RRID:SCR_022275) Copy   

•   Source: SciCrunch Registry

https://github.com/FunctionLab/sei-framework

Web server for systematically predicting sequence regulatory activities and applying sequence information to human genetics data. Provides global map from any sequence to regulatory activities, as represented by sequence classes, and each sequence class integrates predictions for chromatin profiles like transcription factor, histone marks, and chromatin accessibility profiles across wide range of cell types.

Proper citation: sei (RRID:SCR_022571) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   

•   Source: SciCrunch Registry