Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data
نویسندگان
چکیده
منابع مشابه
Mining gene expression data for positive and negative co-regulated gene clusters
MOTIVATION Analysis of gene expression data can provide insights into the positive and negative co-regulation of genes. However, existing methods such as association rule mining are computationally expensive and the quality and quantities of the rules are sensitive to the support and confidence values. In this paper, we introduce the concept of positive and negative co-regulated gene cluster (P...
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Large-scale gene expression studies and genomic sequencing projects are providing vast amounts of information that can be used to identify or predict cellular regulatory processes. Genes can be clustered on the basis of the similarity of their expression profiles or function and these clusters are likely to contain genes that are regulated by the same transcription factors. Searches for cis-reg...
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Motivation: Analysis of gene expression data can provide insights into the time-lagged co-regulations of genes/gene clusters. However, existing methods such as Event Method and Edge Detection Method are inefficient as they only compare two genes each time. More importantly, they lose some important information due to their scoring criterion. In this paper, we propose an efficient algorithm to i...
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ژورنال
عنوان ژورنال: Genome Biology
سال: 2018
ISSN: 1474-760X
DOI: 10.1186/s13059-018-1536-8