[PDF] Top 20 Microarray data analysis: From hypotheses to conclusions using gene expression data
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Microarray data analysis: From hypotheses to conclusions using gene expression data
... the data set at hand, because one has so many ‘predictors’ (all the genes) and usu- ally relatively few ‘outcomes’ (class label of the sam- ...misclassification using the proposed classifier, which is ... See full document
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Combined gene selection methods for microarray data analysis
... First of all, we choose SVMs-lights classification system [10] and C4.5 [17] for experimental study. This choice is based on the following considerations. Consideration of benchmark systems: SVMs and C4.5 have been ... See full document
8
Combined gene selection methods for microarray data analysis
... However, using a one-gene-at-a-time ranking method does not take the re- lationships between genes into ...similar expression levels among classes, and they are redundant since no additional ... See full document
8
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
... two-sample data (separate time- course profiles for each treatment), where the two com- peting hypotheses are represented in a graphical model of two different generative models connected with a gat- ing ... See full document
13
Gene set analysis methods applied to chicken microarray expression data
... the expression ratios for genes previously known to map to this GO BP term and genes that were predicted to belong to this GO ...method using this GO BP term was attempted using the following ... See full document
6
Independent component analysis of Alzheimer's DNA microarray gene expression data
... seen from the clustering dendrogram, the first 11 ICA latent variables captured sufficient biologically significant information from samples ...original data (where the gene expression ... See full document
14
Nonlinear gene cluster analysis with labeling for microarray gene expression data in organ development
... the gene regulatory network underlying optic fissure closure during eye development will be a long process involving genetic analysis of humans with coloboma and studies of eye development in animal ... See full document
13
Meta-analysis of microarray data using a pathway-based approach identifies a 37-gene expression signature for systemic lupus erythematosus in human peripheral blood mononuclear cells
... identify gene expres- sion signatures that differentiate cancer tissues from normal tissues and to predict poor or good patient out- ...cDNA microarray data sets, human hepatocellular ... See full document
10
Microarray data analysis: Gaining biological insights
... in data is greatly ...in microarray datasets most variability can be accounted for by a small number of principal directions ...an expression data set, they do not describe how to best ... See full document
10
GENE EXPRESSION DATA ANALYSIS USING DATA MINING ALGORITHMS FOR COLON CANCER
... of Data mining is used in various medical applications like tumor classification, protein structure prediction, gene classification, cancer classification based on microarray data, clustering ... See full document
7
Detecting microRNA activity from gene expression data
... of gene expression data, such as the generation of clusters or gene lists, is ...on Gene Set Enrichment Analysis (GSEA) ...entire microarray data set and cross ... See full document
42
Original Article Using gene set enrichment analysis to identify new genes involved in sepsis-induced myopathy
... in gene expression on a genome-wide scale. One cave- at of microarray-based approaches is that ge- nes selected for further analysis do not always play a key role in the process being ...on ... See full document
10
Cluster Rasch models for microarray gene expression data
... component analysis, partial least-square regression or com- posite covariate predictor can be used to further reduce the gene dimension to two or three dimensions by taking linear combinations of the ... See full document
13
Identification of Global Gene Expression Shifts Using Microarray Data from Different Biological Conditions
... Recent advances in genomic and post-genomic technologies have provided the opportunity to analyze genomic data publicly available in databases. Several molecular mechanisms can be understood better through the ... See full document
13
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
... cell. Microarray technology looks at many genes at once and determines which are expressed in a particular cell ...type. Using DNA microarray analysis thousands of individual genes can be ... See full document
6
Transcriptome wide based identification of miRs in congenital anomalies of the kidney and urinary tract (CAKUT) in children: the significant upregulation of tissue miR 144 expression
... ence analysis) and supervised CIA (using BGA) was employed to simultaneously analyze mRNA expression levels from microarray and miR target prediction infor- mation in the 3 ′ UTRs of ... See full document
10
Mixture modeling of microarray gene expression data
... genes from GAW15 Problem 1 appear to follow a two- or threecomponent mixture ...tangled using first- and second-order partial correlation ...strategy using the varimax rotation in a factor ... See full document
5
Gene Ontology Analysis of 3D Microarray Gene Expression Data using Hybrid PSO Optimization
... From the input list, 6126 genes are either identified or unidentified but not clear. Unidentified genes shows the annotation providers are still included in the statistics. Also, 1026 duplicates were removed ... See full document
7
Vector Quantization of Microarray Gene Expression Data
... the microarray gene expression data using the three variants of ...cluster analysis of microarray gene expression ...datasets using the application of ... See full document
5
Model based cluster analysis of microarray gene expression data
... observed gene-expression ...followed using the log-transformed data. The original data representing the intensity level (in DLU) for each gene from each of the six ... See full document
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