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In recent years, an increasing emphasis has been put on integrated analysis of gene expression data in the context of PPI, which are widely applied in protein function prediction, functional modules identification, and interaction prediction [ 9, 10].
JP designed and carried out the biocomputational prediction, functional analysis of the predicted sRNAs, and wrote the manuscript.
Integrating high-throughput substrate prediction, functional classification and network analysis, our results suggest that beta-dependent phosphorylation might exert particular regulatory roles in viral infection and biological processes/pathways like apoptosis, DNA repair and RNA metabolism.
Building upon the whole genome operon map developed previously [ 5] we employed additional features for operon prediction: functional similarity of adjacent genes, and conservation of gene order.
This network analysis approach has potential applications to a diverse body of biological data, for example, protein complex prediction, functional prediction, gene variation, and regulatory interactions.
The analytical workflow consisted of three sections: CDS- and 5′UTR-located miRNA target prediction, functional data analysis and SNP-related target identification.
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To verify our hypothesis, based on bioinformatic predictions, functional in vitro studies were performed.
The rapid growth of genomic sequence data starting in early 1980's has spurred the development of computational tools for DNA sequence similarity searches, structural predictions, and functional predictions.
(ii) Isoform-level function predictions and functional relationship predictions.
The above observations indicate that the prediction of functional promoters is very difficult.
Histone H3 acetylation is an epigenetic mark that allows prediction of functional regulatory elements [11].
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