[PDF] Top 20 Detecting relevant changes in high throughput gene expression data
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Detecting relevant changes in high throughput gene expression data
... single gene or spotID), the probability of a type I error is controlled by the significance level chosen by the ...at gene or spotID level does not control the overall probability of making a type I error ... See full document
47
Statistical and Computational Methods for Differential Expression Analysis in High-throughput Gene Expression Data
... for detecting differential expression of spliced transcripts and it only identifies 43 transcripts as significant under default settings ...fold changes of transcript abundances between ASD and ... See full document
159
Computational approaches to identify regulators of plant stress response using high-throughput gene expression data
... the changes in expression, i.e. differences between expression values at consecutive time points, are approx- imated by a linear combination of other genes’ expression ...values. ... See full document
10
High-Throughput Bioinformatics Approaches to Understand Gene Expression Regulation in Head and Neck Tumors.
... clustering expression profiles or determining driver mutations, the identification of which can be very important for prognosis and personalized treatment ...consistent changes across sample ...on ... See full document
166
Investigating cis- and trans-acting elements involved in regulating fetal hemoglobin gene expression using high throughput genetic data
... on detecting whether or not cleavage occurred at five to eight restriction sites when DNA was digested with restriction endonucleases, as shown in Figure 4 (Antonarakis et ...with high-resolution melting ... See full document
94
A high-throughput platform for stem cell niche co-cultures and downstream gene expression analysis.pdf
... integrating high- throughput functional and genetic/genomic ...assess gene expression in single cells and small populations, such as 2-3 cell ...of gene expression changes ... See full document
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High-throughput SuperSAGE for digital gene expression analysis of multiple samples using next generation sequencing
... base changes in the original SuperSAGE data, while such variant sequences were not observed in HT- SuperSAGE (Table ...accurate expression data from tags containing homopolymer sequences than ... See full document
8
Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.
... genes expression as they can alter the structure and function of cellular ...more relevant in CLL with the identification of muta- tions in SF3B1, a splicing factor in a small subset of CLL patients [9] ... See full document
15
Discovery of relevant response in infected potato plants from time series of gene expression data
... Discussion High throughput gene expression profiling has emerged over the last decades as one of the most important and powerful approaches in life science ...temporal changes in mRNA ... See full document
14
Gene expression changes in normal haematopoietic cells.
... epigenetic changes in hematopoietic cells. High‐throughput technology for examining mRNA, or total RNA, expression has been in use for over a ...examined expression of a limited number ... See full document
37
A method for high throughput gene expression signature analysis
... Background Gene expression signatures comprised of tens of genes have been found to be predictive of disease type and patient response to therapy, and have been informative in countless experiments ... See full document
6
Improving Novel Gene Discovery in High-Throughput Gene Expression Datasets
... timepoint) high-throughput gene expression experiments, the most common first analysis step to discover novel genes is to filter out genes based on their degree of differential ... See full document
139
Collective analysis of multiple high-throughput gene expression datasets
... Figure 3.5 (a) shows a sample M-N scatter plot. Each point on this plot, regardless of its shape and colour, represents a single non-empty cluster. The one closest to the top left corner in Euclidean distance is marked ... See full document
157
Detecting microRNA activity from gene expression data
... tissue expression data were also downloaded from the GEO database in the form of raw data ...the gene prediction software and the hgu133plus2 gene set was the same as ... See full document
42
Detecting relevant changes in time series models
... no relevant structural break have a very simple asymptotic distribution, namely a normal ...a relevant change in the mean, variance, parameters in a linear regression model and distribution ...a data ... See full document
42
Detecting changes in high frequency data streams, with applications
... the data stream, which can be done in a computationally efficient ...quickly changes are detected, but no attention is given to the problem of false positives, or assessing the sig- nificance of ... See full document
195
Detecting non allelic homologous recombination from high throughput sequencing data
... Results We developed a model for detecting NAHR from paired- end read data that addresses many of the issues that typically arise due to repeats. Our model rigorously ana- lyzes read depth inside repeats, ... See full document
19
A Methodology for Biologically Relevant Pattern Discovery from Gene Expression Data
... to gene expression data, we can get rather dense boolean con- texts that are hard to process if further user-defined constraints are not only specified but also pushed deeply into the extraction ... See full document
12
Differential gene expression in disease: a comparison between high-throughput studies and the literature
... a gene X using disease and human gene annotations from NCBI’ s PubTator (down- load 2016-01-25) ...of gene X, disease Y (or abbreviation) and trigger word (or ...Undefined expression ... See full document
10
High Throughput Method for Detecting Genomic Deletion Polymorphisms
... Division of Infectious Diseases and Geographic Medicine, Department of Medicine, 1 and Department of Microbiology and Immunology, 2 Stanford University Medical Center, Stanford, California Received 13 October ... See full document
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