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Determining a detectable threshold of signal intensity in cDNA microarray based on accumulated distribution
1State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University, Shanghai 200433, PR China.
Journal of Biochemistry and Molecular Biology
|December 9, 2003
Summary
This study introduces a new method to find detectable thresholds in microarray data, improving gene filtering for more reliable data mining. The approach effectively handles weak signals, enhancing data reproducibility.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Microarray data analysis presents challenges in handling weak signals.
- Identifying and filtering genes with unreliable information is crucial for accurate data mining.
Purpose of the Study:
- To propose a novel detectable threshold finding method for microarray data.
- To enhance the reliability and reproducibility of data for subsequent analysis.
Main Methods:
- The study is based on a bent piecewise linear accumulated distribution commonly observed in microarray data.
- A new threshold finding method is developed to filter genes with unreliable information.
Main Results:
- The proposed method effectively identifies and filters genes with weak or unreliable signals.
- Implementation of the method leads to more reliable and reproducible microarray data.
Conclusions:
- The developed detectable threshold finding method addresses a key challenge in microarray data mining.
- This approach improves the quality of data, facilitating more robust downstream analyses.