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Bayesian biclustering of gene expression data [PDF]
BMC Genomics, 2008 Background Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions ...
Liu Jun S, Gu Jiajun
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Identifying gene interaction enrichment for gene expression data. [PDF]
PLoS ONE, 2009 Gene set analysis allows the inclusion of knowledge from established gene sets, such as gene pathways, and potentially improves the power of detecting differentially expressed genes.
Jigang Zhang, Jian Li, Hong-Wen Deng
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Gene Expression Databases and Data Mining [PDF]
BioTechniques, 2003 The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study.
Pascale Anderle +7 more
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CoXpress: differential co-expression in gene expression data [PDF]
BMC Bioinformatics, 2006 Background Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find groups of genes that behave similarly across a dataset.
Watson Michael
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Meta-Analysis of RNA-Seq and Microarray Expression Data to Identify Genes Effective in Sheep Muscle Growth and Development [PDF]
پژوهشهای علوم دامی ایران, 2023 Introduction: Among different sheep breeds in the world, the Texel breed is known as a meaty and muscular breed. Skeletal muscle growth is a step-by-step and exponential process from differentiation, development and maturation, which is regulated by gene
Fahime Mohammadi +2 more
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Characterization of RNA in exosomes secreted by human breast cancer cell lines using next-generation sequencing [PDF]
PeerJ, 2013 Exosomes are nanosized (30–100 nm) membrane vesicles secreted by most cell types. Exosomes have been found to contain various RNA species including miRNA, mRNA and long non-protein coding RNAs. A number of cancer cells produce elevated levels of exosomes.
Piroon Jenjaroenpun +5 more
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Gene expression data preprocessing [PDF]
Bioinformatics, 2003 Abstract Summary: We present an interactive web tool for preprocessing microarray gene expression data. It analyses the data, suggests the most appropriate transformations and proceeds with them after user agreement. The normal preprocessing steps include scale transformations, management of missing values, replicate handling, flat ...
Javier Herrero +2 more
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Error Distribution for Gene Expression Data [PDF]
Statistical Applications in Genetics and Molecular Biology, 2005 We present a new instance of Laplace's second Law of Errors and show how it can be used in the analysis of data from microarray experiments. This error distribution is shown to fit microarray expression data much better than a normal distribution. The use of this distribution in a parametric bootstrap leads to more powerful tests as we show that the t ...
Purdom, Elizabeth, Holmes, Susan P.
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Finding Groups in Gene Expression Data [PDF]
BioMed Research International, 2005 The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large‐scale, high‐throughput investigations of gene activity and have
Hand, DJ, Heard, NA
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Implementing Gene Expression Programming in the Parallel Environment for Big Datasets’ Classification [PDF]
Vietnam Journal of Computer Science, 2019 The paper investigates a Gene Expression Programming (GEP)-based ensemble classifier constructed using the stacked generalization concept. The classifier has been implemented with a view to enable parallel processing with the use of Spark and SWIM — an ...
Joanna Jȩdrzejowicz +2 more
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