Analysis of Mutation in CancerThis is a featured page

Massive sequencing efforts are currently underway to identify point mutations in a variety of genes in cancer. The sheer volume of data produced requires automated systems to read sequence data, and to compare the sequencing results to the known sequence of the human genome, including known germline polymorphisms. Oligonucleotide microarrays, including comparative genomic hybridization and single nucleotide polymorphism arrays, able to probe simultaneously up to several hundred thousand sites throughout the genome are being used to identify chromosomal gains and losses in cancer. Hidden Markov model and change-point analysis methods are being developed to infer real copy number changes from often noisy data. Further informatics approaches are being developed to understand the implications of lesions found to be recurrent across many tumors. Some modern tools (e.g. Quantum 3.1 ) provide tool for changing the protein sequence at specific sites through alterations to its amino acids and predict changes in the bioactivity after mutations.


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deveshl 		Latest page update: made by deveshl , Feb 16 2007, 6:47 AM EST (about this update About This Update deveshl Edited by deveshl

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