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Cell Lines

Cell Lines

A cell line is a population of cells grown in vitro that can be subcultured over several generations. Normal cells cease to divide after a certain number of cell divisions, a process known as replicative senescence. This number, called the Hayflick limit, was conceptualized by Leonard Hayflick in 1961 when he observed that fetal cells grown in culture could only divide 40-60 times. This limit is due to the shortening of the telomeres during each round of cell division, preventing cell division...

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Related Experiment Video

Updated: Jul 3, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Protocol to set up the CellMinerCDB pharmacogenomics analysis web application with custom cell line data.

Fathi Elloumi¹, Camille Tlemsani², Christine M Heske³

¹Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.

|September 26, 2025

Summary

This study details setting up CellMiner Cross-Database (CellMinerCDB), an application for cancer cell line data analysis. The protocol enables molecular and pharmacological data integration and analysis for cancer research.

Keywords:

Bioinformatics Cancer Genomics Health Sciences

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Area of Science:

Bioinformatics
Genomics
Pharmacology

Background:

Cancer cell line data integration is crucial for research.
Analyzing molecular and pharmacological profiles aids drug discovery.
Existing tools may lack comprehensive cross-database analysis capabilities.

Purpose of the Study:

To provide a detailed protocol for setting up CellMiner Cross-Database (CellMinerCDB).
To enable integrated analysis of molecular and pharmacological data across human cancer cell lines.
To demonstrate the application using sarcoma data.

Main Methods:

Software installation and configuration.
Preparation of compatible molecular and pharmacological datasets.
Deployment of the CellMinerCDB application for data analysis.

Main Results:

A functional CellMinerCDB setup enabling data integration.
Successful demonstration of univariate and multivariate analyses.
Customizable configuration for diverse cancer datasets.

Conclusions:

CellMinerCDB provides a robust platform for cross-database cancer cell line analysis.
The detailed protocol facilitates the implementation of this powerful analytical tool.
This facilitates deeper insights into cancer biology and therapeutic strategies.