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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

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   

•   Source: SciCrunch Registry

http://life.ccs.miami.edu/life/

LIFE search engine contains data generated from LINCS Pilot Phase, to integrate LINCS content leveraging semantic knowledge model and common LINCS metadata standards. LIFE makes LINCS content discoverable and includes aggregate results linked to Harvard Medical School and Broad Institute and other LINCS centers, who provide more information including experimental conditions and raw data. Please visit LINCS Data Portal.

Proper citation: LINCS Information Framework (RRID:SCR_003937) Copy   

•   Source: SciCrunch Registry

http://snyderome.stanford.edu/

Data set generated by personal omics profiling of Dr. Michael Snyder at Stanford University. It combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. The analysis revealed various medical risks, including type II diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions.

Proper citation: iPOP (RRID:SCR_008991) 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://www.ngvbcc.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. Archiving services, insertional site analysis, pharmacology and toxicology resources, and reagent repository for academic investigators and others conducting gene therapy research. Databases and educational resources are open to everyone. Other services are limited to gene therapy investigators working in academic or other non-profit organizations. Stores reserve or back-up clinical grade vector and master cell banks. Maintains samples from any gene therapy related Pharmacology or Toxicology study that has been submitted to FDA by U.S. academic investigator that require storage under Good Laboratory Practices. For certain gene therapy clinical trials, FDA has required post-trial monitoring of patients, evaluating clinical samples for evidence of clonal expansion of cells. To help academic investigators comply with this FDA recommendation, the NGVB offers assistance with clonal analysis using LAM-PCR and LM-PCR technology.

Proper citation: National Gene Vector Biorepository (RRID:SCR_004760) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://pypi.org/project/pmlb/

Python wrapper for Penn Machine Learning Benchmark data repository. Large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms. Part of PyPI https://pypi.org/

Proper citation: Penn machine learning benchmark repository (RRID:SCR_017138) 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://github.com/BioDepot/nbdocker

Software tool as Jupyter Notebook extension for Docker. Each Docker container encapsulates its individual computing environment to allow different programming languages and computing environments to be included in one single notebook, provides user to document code as well as computing environment.

Proper citation: nbdocker (RRID:SCR_017159) Copy   

•   Source: SciCrunch Registry

https://sites.cscc.unc.edu/aric/

Platform for prospective epidemiologic study conducted in four U.S. communities. One of most significant and longest running heart health studies and is the largest study of heart health in African Americans. ARIC investigates risk factors for heart disease and stroke, and connections between cardiovascular and cognitive health. ARIC includes two parts: Cohort Component and Community Surveillance Component. Cohort Component began in 1987, and each ARIC field center randomly selected and recruited cohort sample of individuals aged 45-64 from defined population in their community, to receive extensive examinations, including medical, social, and demographic data. In Community Surveillance Component, four communities are investigated to determine long term trends in hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years.

Proper citation: Atherosclerosis Risk in Communities (RRID:SCR_021769) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://starnet.mssm.edu/

Web interactive browser to visualize data and perform gene set enrichment analysis along with gene and SNP lookup. Web interface used to query STARNET datasets and downstream analysis which includes RNAseq from 7 tissues: blood, free internal mammary artery (MAM), atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV). Paired SNP genotyping data is included and utilized for tissue expression quantitative trait loci (eQTL), CAD heritability (H2), co-expression networks and gene regulatory networks.

Proper citation: STARNET (RRID:SCR_025238) Copy   

•   Source: SciCrunch Registry

https://github.com/ccipd/MRQy

Software quality assurance and checking tool for quantitative assessment of magnetic resonance imaging and computed tomography data. Used for quality control of MR imaging data.

Proper citation: MRQy (RRID:SCR_025779) Copy   

•   Source: SciCrunch Registry

https://pypi.org/project/SpaGCN/

Software graph convolutional network to integrate gene expression and histology to identify spatial domains and spatially variable genes. SpaGCN integrates information from gene.

Proper citation: SpaGCN (RRID:SCR_025978) Copy   

•   Source: SciCrunch Registry

https://www.c4r-nih.org

Portal provides information about nationwide study of more than 50,000 individuals to determine factors that predict disease severity and long-term health impacts of COVID-19.

Proper citation: Collaborative Cohort of Cohorts for COVID-19 Research (RRID:SCR_026322) Copy   

•   Source: SciCrunch Registry

https://github.com/kharchenkolab/conos

Software R package for joint analysis of multiple single-cell RNA-seq datasets. Used to wire together large collections of single-cell RNA-seq datasets, which allows for both identification of recurrent cell clusters and propagation of information between datasets in multi-sample or atlas-scale collections.

Proper citation: Conos (RRID:SCR_026381) 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

https://github.com/McGranahanLab/TcellExTRECT

Software R package to calculate T cell fractions from WES data from hg19 or hg38 aligned genomes.

Proper citation: T Cell ExTRECT (RRID:SCR_027742) Copy   

•   Source: SciCrunch Registry