# COBRA Preprint Series Year Paper Exploration of distributional models for a novel intensity-dependent normalization

@inproceedings{Lama2013COBRAPS, title={COBRA Preprint Series Year Paper Exploration of distributional models for a novel intensity-dependent normalization}, author={Nicola Lama and Patrizia Boracchi and Elia Biganzoli}, year={2013} }

- Published 2013

Currently used gene intensity-dependent normalization methods, based on regression smoothing techniques, usually approach the two problems of location bias detrending and data re-scaling without taking into account the censoring characteristic of certain gene expressions produced by experiment measurement constraints or by previous normalization steps. Moreover, the bias vs variance balance control of normalization procedures is not often discussed but left to the user’s experience. Here an… CONTINUE READING

#### References

##### Publications referenced by this paper.

SHOWING 1-10 OF 37 REFERENCES

## Statistics for microarrays

VIEW 5 EXCERPTS

HIGHLY INFLUENTIAL

## A Software Tool for the Exponential Power Distribution: The normalp Package

VIEW 4 EXCERPTS

HIGHLY INFLUENTIAL

## Error distribution for gene expression data

VIEW 5 EXCERPTS

HIGHLY INFLUENTIAL

## Gene expression profiling predicts clinical outcome of breast cancer

VIEW 7 EXCERPTS

HIGHLY INFLUENTIAL

## Ratio-based decisions and the quantitative analysis of cDNA microarray images.

VIEW 6 EXCERPTS

HIGHLY INFLUENTIAL

## Randomized Quantile Residuals.

VIEW 6 EXCERPTS

HIGHLY INFLUENTIAL

## The limits of log-ratios

VIEW 3 EXCERPTS

HIGHLY INFLUENTIAL

## A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

VIEW 3 EXCERPTS

HIGHLY INFLUENTIAL

## A Model for Measurement Error for Gene Expression Arrays

VIEW 3 EXCERPTS

HIGHLY INFLUENTIAL

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