Pathways to the analysis of microarray data.

By R. Keira Curtis, Matej Oresic, Antonio Vidal-Puig. Trends in Biotechnology, 2005

331 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/dea98c6314b8c49c45d26bab3f5c3e8ba7343b64

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In Molecular Biology

Citations in the corpus

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists (2008, neutral): “number of genes in the list that hit a given biology class as compared to pure random chance, can be performed with the aid of some common and well-known statistical methods (11,12,76), including Chi-square, Fisher’s exact test, Binomial probability and Hypergeometric distribution, etc.”
A Review of Ensemble Methods in Bioinformatics (2010, background): “Lastly, genes are connected by pathways and functioning in groups, and therefore, there is a growing trend to analyze microarray data at the pathway level [47].”
The ConsensusPathDB interaction database: 2013 update (2012, methodology): “Over the past decade, pathway over-representation/enrichment analysis of gene lists has proven a very useful tool for interpreting large-scale transcriptomics and proteomics data (30).”
Concept annotation in the CRAFT corpus (2012, background): “In particular, calculations of enrichment of Gene Ontology (GO) terms in sets of differentially expressed genes are widely used [8-10], and more sophisticated uses of formal knowledge representations in data analysis are beginning to be published ( e.g. , [11]).”
LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data (2009, methodology): “Several statistical methods are commonly used in this context, but the question of the optimal approach has still not been resolved.”
Pathway-based approaches for analysis of genomewide association studies. (2007, background): “Rather than focusing on individual genes having the strongest evidence of differential expression, these pathwaybased approaches typically rank all genes by their significance of differential expression, and then look for whether a particular group of genes is enriched at one end of the ranked list ”