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  • Search: isPartOf:"Statistical Applications in Genetics and Molecular Biology"
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multiple testing 28 gene expression 21 microarray 15 microarrays 14 bootstrap 11 false discovery rate 11 classification 10 null distribution 10 variable selection 10 cross-validation 9 Type I error rate 8 asymptotic control 8 model selection 8 prediction 7 Adjusted p-value 6 empirical Bayes 6 Microarrays 5 censoring 5 consistency 5 differential expression 5 machine learning 5 maximum likelihood 5 meta-analysis 5 multiple comparisons 5 normalization 5 EM algorithm 4 FDR 4 Markov chain Monte Carlo 4 SNP 4 augmentation 4 case-control 4 clustering 4 cut-off 4 family-wise error rate 4 generalized family-wise error rate 4 genetics 4 hidden Markov model 4 loss-based estimation 4 mass spectrometry 4 microarray analysis 4
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Undetermined 775
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Article 775
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Undetermined 775
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Laan, Mark van der 35 van der Laan Mark J. 19 Dudoit, Sandrine 12 Hubbard, Alan 10 Pollard, Katherine 9 Rongling, Wu 9 Sinisi, Sandra 8 Bickel David R. 7 Keles, Sunduz 7 R, Segal Mark 7 Sandrine, Dudoit 7 Birkner, Merrill 6 Derek, Gordon 6 Dirk, Husmeier 6 J, Finch Stephen 6 Joseph, Beyene 6 Segal, Mark 6 Hubbard Alan E. 5 Sunduz, Keles 5 Thomas, Lengauer 5 Tomasz, Burzykowski 5 Ziv, Shkedy 5 Beyene, Joseph 4 Bickel, David 4 Boulesteix, Anne-Laure 4 Brad, McNeney 4 Burzykowski, Tomasz 4 Chad, Haynes 4 Dan, Lin 4 Eisen, Michael 4 Hongyu, Zhao 4 Jinko, Graham 4 Paul, Joyce 4 Pollard Katherine S. 4 Polley, Eric 4 Shkedy, Ziv 4 Smith, Martyn 4 Sylvia, Richardson 4 Tibshirani Robert J. 4 Wu, Rongling 4
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Statistical Applications in Genetics and Molecular Biology 775
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RePEc 775
Showing 441 - 450 of 775
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Support Vector Machine Approach to Separate Control and Breast Cancer Serum Samples
V, Pham Thang; A, van de Wiel Mark; R, Jimenez Connie - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 2, pp. 1-11
The paper presents two analyzes of the MALDI-TOF mass spectrometry dataset. Both analyzes use the support vector machine as a tool to build a prediction model. The first analysis which is our contribution to the competition uses the given spectra data without further processing. In the second...
Persistent link: https://www.econbiz.de/10008460193
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Coalescent Time Distributions in Trees of Arbitrary Size
Sam, Efromovich; Laura, Salter Kubatko - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 1-30
The relationship between speciation times and the corresponding times of gene divergence is of interest in phylogenetic inference as a means of understanding the past evolutionary dynamics of populations and of estimating the timing of speciation events. It has long been recognized that gene...
Persistent link: https://www.econbiz.de/10008460194
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Reducing Spatial Flaws in Oligonucleotide Arrays by Using Neighborhood Information
Manuel, Arteaga-Salas Jose; P, Harrison Andrew; Upton … - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 1-19
We address the problem of detection and correction of spatial flaws in oligonucleotide microarrays. We present two similar procedures, of which one is intended solely for use with replicates and the other has wider applicability. By constructing a set of replicates, with one realistically...
Persistent link: https://www.econbiz.de/10008460195
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Breast Cancer Diagnosis from Proteomic Mass Spectrometry Data: A Comparative Evaluation
J, Hand David - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 2, pp. 1-23
The performance results of a wide range of different classifiers applied to proteomic mass spectra data, in a blind comparative assessment organised by Bart Mertens, are reviewed. The different approaches are summarised, issues of how to evaluate and compare the predictions are described, and...
Persistent link: https://www.econbiz.de/10008460198
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Correcting the Estimated Level of Differential Expression for Gene Selection Bias: Application to a Microarray Study
Bickel David R. - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 1-27
The level of differential gene expression may be defined as a fold change, a frequency of upregulation, or some other measure of the degree or extent of a difference in expression across groups of interest. On the basis of expression data for hundreds or thousands of genes, inferring which genes...
Persistent link: https://www.econbiz.de/10008460201
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Addressing the Shortcomings of Three Recent Bayesian Methods for Detecting Interspecific Recombination in DNA Sequence Alignments
Dirk, Husmeier; Mantzaris Alexander V. - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 1-41
We address a potential shortcoming of three probabilistic models for detecting interspecific recombination in DNA sequence alignments: the multiple change-point model (MCP) of Suchard et al. (2003), the dual multiple change-point model (DMCP) of Minin et al. (2005), and the phylogenetic...
Persistent link: https://www.econbiz.de/10008460204
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Estimating Number of Clusters Based on a General Similarity Matrix with Application to Microarray Data
Shafagh, Fallah; David, Tritchler; Joseph, Beyene - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 1-25
Many clustering methods require that the number of clusters believed present in a given data set be specified a priori, and a number of methods for estimating the number of clusters have been developed. However, the selection of the number of clusters is well recognized as a difficult and open...
Persistent link: https://www.econbiz.de/10008460210
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Modeling DNA Methylation in a Population of Cancer Cells
Siegmund Kimberly D.; Paul, Marjoram; Darryl, Shibata - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 1-23
Little is known about how human cancers grow because direct observations are impractical. Cancers are clonal populations and the billions of cancer cells present in a visible tumor are progeny of a single transformed cell. Therefore, human cancers can be represented by somatic cell ancestral...
Persistent link: https://www.econbiz.de/10008460224
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Classification of Breast Cancer versus Normal Samples from Mass Spectrometry Profiles Using Linear Discriminant Analysis of Important Features Selected by Random Forest
Somnath, Datta - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 2, pp. 1-14
We present our approach to classifying the processed proteomic data that were made available to the participants of the classification competition. Although classification of the spectra was the goal of the competition we feel that proteomic applications to cancer biomarker studies make certain...
Persistent link: https://www.econbiz.de/10008460225
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Pattern Classification of Phylogeny Signals
Xiaofei, Shi; Hong, Gu; Chris, Field - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 1-22
In this paper we propose the minimum entropy clustering (MEC) method for clustering genes based on their phylogenetic signals. This entropy based method will cluster two genes together when their concatenation can decrease the entropy. An integral feature of MEC is that it chooses the number of...
Persistent link: https://www.econbiz.de/10008460238
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