Search results for " microarray data"
showing 6 items of 6 documents
Differential expression of specific microRNA and their targets in acute myeloid leukemia
2010
Acute myeloid leukemia (AML) the most common acute leukemia in adults is characterized by various cytogenetic and molecular abnormalities. However, the genetic etiology of the disease is not yet fully understood. MicroRNAs (miRNA) are small noncoding RNAs which regulate the expression of target mRNAs both at transcriptional and translational level. In recent years, miRNAs have been identified as a novel mechanism in gene regulation, which show variable expression during myeloid differentiation. We studied miRNA expression of leukemic blasts of 29 cases of newly diagnosed and genetically defined AML using quantitative reverse transcription polymerase chain reaction (RT-PCR) for 365 human miR…
A statistical calibration model for Affymetrix probe level data
2009
Gene expression microarrays allow a researcher to measure the simultaneous response of thousands of genes to external conditions. Affymetrix GeneChip{ $Ⓡ$} expression array technology has become a standard tool in medical research. Anyway, a preprocessing step is usually necessary in order to obtain a gene expression measure. Aim of this paper is to propose a calibration method to estimate the nominal concentration based on a nonlinear mixed model. This method is an enhancement of a method proposed in Mineo et al. (2006). The relationship between raw intensities and concentration is obtained by using the Langmuir isotherm theory.
Mixing modelling ideas for microarray data
2009
Mixed models have typically been used for modelling structural effects in presence of random variations. These type of models can be used rather naturally when we work with microarray data. In this paper, we shall look at two extensions of the usual mixed effect models.
Studying Nucleosomes Positioning by a Multi-Layer Model
2007
Eukaryotic DNA is packaged into a highly compact and dynamic structure called chromatin. While this packaging allows the cell to organize a large and complex genome in the nucleus, it can also block the access of transcription factors and other proteins to DNA. Nucleosomes are the fundamental repeating units of eukaryotic chromatin. Nucleosome position can be regulated in vivo by multi-subunit chromatin remodeling complexes, and their position can influence gene expression in eukaryotic cells. Alterations in chromatin structure, and hence in nucleosome organization, can result in a variety of diseases, including cancer, highlighting the need to achieve a better understanding of the molecula…
Speeding up the Consensus Clustering methodology for microarray data analysis
2010
Abstract Background The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose…
Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of Merit, Gap Statistic…
2008
Abstract Background Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with regard to the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures available in the literature, new ones have been recently proposed, some of them specifically for microarray data. Results We consider five such measures: Clest, Consensus (Consensus Clustering), FOM (Figure of Merit), Gap (Gap Statistics) and ME (Model Explorer), in addition to the classic WCSS (Within Cluster…