Modeling Mutual Exclusivity of Cancer Mutations
نویسندگان
چکیده
منابع مشابه
Modeling Mutual Exclusivity of Cancer Mutations
In large collections of tumor samples, it has been observed that sets of genes that are commonly involved in the same cancer pathways tend not to occur mutated together in the same patient. Such gene sets form mutually exclusive patterns of gene alterations in cancer genomic data. Computational approaches that detect mutually exclusive gene sets, rank and test candidate alteration patterns by r...
متن کاملText S1 Modeling mutual exclusivity of cancer mutations
Here, for convenience, the mutually mutated gene is specified by a vector of binary random variables H = (H1, . . . ,Hn), only one of which can be assigned value 1 at a time: P (Hg = 1) = 1 n , and Hg = 1 implies that Hg′ = 0 for all g ′ 6= g. To obtain P (y|θ), the observed likelihood for observation y (equation 1 in the main text), we need to marginalize the hidden variables out. This likelih...
متن کاملMutual Exclusivity 1 Running head : MUTUAL EXCLUSIVITY IN AUTISM
While there is ample evidence that children treat words as mutually exclusive, the cognitive basis of this bias is widely debated. We focus on the distinction between pragmatic and lexical constraints accounts. High-functioning children with autism spectrum disorders (ASD) offer a unique perspective on this debate, as they acquire substantial vocabularies despite impoverished social-pragmatic s...
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Motivation Mutual exclusivity is a widely recognized property of many cancer drivers. Knowledge about these relationships can provide important insights into cancer drivers, cancer-driving pathways and cancer subtypes. It can also be used to predict new functional interactions between cancer driving genes and uncover novel cancer drivers. Currently, most of mutual exclusivity analyses are prefo...
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The words that children learn can be characterized as a semantic network, with links connecting related words. Recent analyses have shown these networks to have smallworld structure, with a few highly-connected hub words facilitating short paths between otherwise distant words. This structure contributes to network robustness, and differences in structure can predict differences in language lea...
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ژورنال
عنوان ژورنال: PLoS Computational Biology
سال: 2014
ISSN: 1553-7358
DOI: 10.1371/journal.pcbi.1003503