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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

Synthetic Biology

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...

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Related Experiment Video

Updated: Mar 15, 2026

Generation of Microtumors Using 3D Human Biogel Culture System and Patient-derived Glioblastoma Cells for Kinomic Profiling and Drug Response Testing

Generation of Microtumors Using 3D Human Biogel Culture System and Patient-derived Glioblastoma Cells for Kinomic Profiling and Drug Response Testing

Published on: June 9, 2016

A Synthetic Kinome Microarray Data Generator.

Farhad Maleki¹, Anthony Kusalik²

¹Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. farhad.maleki@usask.ca.

Microarrays (Basel, Switzerland)

|September 8, 2016

Summary

This summary is machine-generated.

This study introduces a novel method for generating synthetic kinome array data, crucial for evaluating analysis techniques. This approach addresses the lack of real-world data, enabling better comparison of phosphorylation analysis methods.

Keywords:

heteroscedasticity of variance kinome array normalization synthetic data

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High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries

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Published on: August 12, 2019

Area of Science:

Biochemistry
Proteomics
Bioinformatics

Background:

Cellular signaling relies on protein phosphorylation and dephosphorylation.
Kinome arrays enable high-throughput measurement of protein phosphorylation activity.
Analyzing kinome array data requires robust evaluation methods, hindered by a lack of standardized datasets.

Purpose of the Study:

To develop a methodology for generating synthetic kinome array data.
To create realistic datasets that preserve characteristics of real kinome experiments.
To facilitate the evaluation and comparison of data analysis techniques for kinome arrays.

Main Methods:

A novel methodology for synthetic kinome data generation is proposed.
The method utilizes actual intensity measurements from kinome microarray experiments.
The synthetic data generation preserves subtle characteristics of real experimental data.

Main Results:

The proposed methodology successfully generates synthetic kinome array data.
The synthetic data is suitable for evaluating downstream statistical techniques.
The utility is demonstrated by comparing variance stabilization methods for heterogeneous variance in kinome data.

Conclusions:

The developed methodology provides a valuable tool for analyzing kinome array data.
It enables critical comparison of analytical methods, particularly for addressing variance issues.
This facilitates advancements in understanding cellular phosphorylation pathways.