Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data,[1] including both DNA and RNA sequence as well as other "post-genomic" data (i.e., experimental data obtained with technologies that require the genome sequence, such as genomic DNA microarrays). These, in combination with computational and statistical approaches to understanding the function of the genes and statistical association analysis, this field is also often referred to as Computational and Statistical Genetics/genomics. As such, computational genomics may be regarded as a subset of bioinformatics and computational biology, but with a focus on using whole genomes (rather than individual genes) to understand the principles of how the DNA of a species controls its biology at the molecular level and beyond. With the current abundance of massive biological datasets, computational studies have become one of the most important means to biological discovery.[2]
^Koonin EV (March 2001). "Computational genomics". Current Biology. 11 (5): R155–8. doi:10.1016/S0960-9822(01)00081-1. PMID 11267880. S2CID 17202180.
^"Computational Genomics and Proteomics at MIT". Archived from the original on 2018-03-22. Retrieved 2006-12-29.
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contained in a string, typically considered for DNA sequences in computationalgenomics. This disambiguation page lists articles associated with the title...
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