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In page Bioinformatics:

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In cancer, the genomes of affected cells are rearranged in complex or unpredictable ways. In addition to single-nucleotide polymorphism arrays identifying point mutations that cause cancer, oligonucleotide microarrays can be used to identify chromosomal gains and losses (called comparative genomic hybridization). These detection methods generate terabytes of data per experiment. The data is often found to contain considerable variability, or noise, and thus Hidden Markov model and change-point analysis methods are being developed to infer real copy number changes.[citation needed]