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URL: https://www.zurich.ibm.com/cellcycletracer/
Proper Citation: CellCycleTRACER (RRID:SCR_017128)
Description: Software tool as supervised machine learning algorithm that classifies and sorts single cell mass cytometry data according to their cell cycle, which allows to correct for cell cycle state and cell volume heterogeneity. Reveals signaling relationships and cell heterogeneity that were otherwise masked. Computational method to quantify cell cycle and cell volume variability.
Resource Type: data access protocol, data analysis software, data processing software, software application, software resource, web service
Defining Citation: PMID:29434325
Keywords: classify, sort, single, cell, mass, cytometry, data, cycle, state, volume, heterogeneity, quantify, volume, variability
Funding: European Research Council ; NIDDK UC4 DK108132; SNSF ; SystemsX MetastasiX grant
Availability: Free, Restricted
Resource Name: CellCycleTRACER
Resource ID: SCR_017128
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Source: SciCrunch Registry (RRID:SCR_005400)
Description: Interactive portal for finding and submitting biomedical resources. Resources within SciCrunch have assigned RRIDs which are used to cite resources in scientific manuscripts. SciCrunch Registry, formerly NIF Registry, provides resources catalog. Allows to add new resources. Allows edit existing resources after registration. Curators are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping contents current.
URL: https://rrid.site/rin/sources/SCR_005400
The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant U24DK097771.
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