Combining Disparate Data Types: Protein Sequences and Protein Structures
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With the development of high-throughput, next-generation sequencing and other advanced technologies, a large number of gene expression profiles have been produced. Many of these profiles are available from public databases [1-3]. A challenging research problem that has drawn a lot of attention in the past is to infer gene regulatory networks from the expression data. A gene regulatory network is represented by a directed graph, in which nodes represent transcription factors or mRNA with edges showing transcriptional regulatory relationships between two nodes.
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This article is published as Kejue Jia and Robert L. Jernigan (2015) Combining Disparate Data Types: Protein Sequences and Protein Structures. J Data Mining Genomics Proteomics 6:e117. doi: 10.4172/2153-0602.1000e117. Posted with permission.