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Statistical tools for synthesizing lists of differentially expressed features in related experiments.

Blangiardo M, Richardson S.

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Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments.

Zhao H, Chan KL, Cheng LM, Yan H.

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Comments on 'Bayesian hierarchical error model for analysis of gene expression data'.

Wu XL, Forney LJ, Joyce P.

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Bayesian hierarchical model for identifying changes in gene expression from microarray experiments.

Broët P, Richardson S, Radvanyi F.

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A unified approach for simultaneous gene clustering and differential expression identification.

Yuan M, Kendziorski C.

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A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays.

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A powerful method for detecting differentially expressed genes from GeneChip arrays that does not require replicates.

Hein AM, Richardson S.

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The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies.

Shi L, Jones WD, Jensen RV, Harris SC, Perkins RG, Goodsaid FM, Guo L, Croner LJ, Boysen C, Fang H, Qian F, Amur S, Bao W, Barbacioru CC, Bertholet V, Cao XM, Chu TM, Collins PJ, Fan XH, Frueh FW, Fuscoe JC, Guo X, Han J, Herman D, Hong H, Kawasaki ES, Li QZ, Luo Y, Ma Y, Mei N, Peterson RL, Puri RK, Shippy R, Su Z, Sun YA, Sun H, Thorn B, Turpaz Y, Wang C, Wang SJ, Warrington JA, Willey JC, Wu J, Xie Q, Zhang L, Zhang L, Zhong S, Wolfinger RD, Tong W.

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Tail posterior probability for inference in pairwise and multiclass gene expression data.

Bochkina N, Richardson S.

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Bayesian modeling of differential gene expression.

Lewin A, Richardson S, Marshall C, Glazier A, Aitman T.

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Finding differentially expressed genes in two-channel DNA microarray datasets: how to increase reliability of data preprocessing.

Rotter A, Hren M, Baebler S, Blejec A, Gruden K.

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Variance component estimation for mixed model analysis of cDNA microarray data.

Sarholz B, Piepho HP.

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Bayesian modelling of shared gene function.

Sykacek P, Clarkson R, Print C, Furlong R, Micklem G.

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A Bayesian approach to estimation and testing in time-course microarray experiments.

Angelini C, De Canditiis D, Mutarelli M, Pensky M.

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Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks.

Kim CS.

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Quality optimised analysis of general paired microarray experiments.

Kristiansson E, Sjögren A, Rudemo M, Nerman O.

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Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysis.

Nettleton D, Recknor J, Reecy JM.

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Genetic network analysis by quasi-bayesian method.

Yuan A, Chen G, Rotimi C.

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A new outlier removal approach for cDNA microarray normalization.

Wu Y, Yan L, Liu H, Sun H, Xie H.

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Approaches to reduce false positives and false negatives in the analysis of microarray data: applications in type 1 diabetes research.

Wu J, Lenchik NI, Gerling IC.

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