Editing Bioinformatics (section)

===Analysis of mutations in cancer===
{{main|Oncogenomics}}

In [[cancer]], the genomes of affected cells are rearranged in complex or unpredictable ways. In addition to [[single-nucleotide polymorphism]] arrays identifying [[point mutation]]s that cause cancer, [[oligonucleotide]] microarrays can be used to identify chromosomal gains and losses (called [[comparative genomic hybridization]]). These detection methods generate [[terabyte]]s 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|date=June 2023}}

Two important principles can be used to identify cancer by mutations in the [[exome]]. First, cancer is a disease of accumulated somatic mutations in genes. Second, cancer contains driver mutations which need to be distinguished from passengers.<ref>{{cite journal | vauthors = Vazquez M, de la Torre V, Valencia A | title = Chapter 14: Cancer genome analysis | journal = PLOS Computational Biology | volume = 8 | issue = 12 | pages = e1002824 | date = 2012-12-27 | pmid = 23300415 | pmc = 3531315 | doi = 10.1371/journal.pcbi.1002824 | bibcode = 2012PLSCB...8E2824V | doi-access = free }}</ref>

Further improvements in bioinformatics could allow for classifying types of cancer by analysis of cancer driven mutations in the genome. Furthermore, tracking of patients while the disease progresses may be possible in the future with the sequence of cancer samples. Another type of data that requires novel informatics development is the analysis of [[lesion]]s found to be recurrent among many tumors.<ref>{{cite book | vauthors = Hye-Jung EC, Jaswinder K, Martin K, Samuel AA, Marco AM | veditors = Dellaire G, Berman JN, Arceci RJ | title= Cancer Genomics |date=2014 |publisher=Academic Press |location=Boston (US) |isbn=978-0-12-396967-5 |pages=13–30 |chapter=Second-Generation Sequencing for Cancer Genome Analysis |doi=10.1016/B978-0-12-396967-5.00002-5}}</ref>