Abstract
With the development of Next-generation DNA sequencing technologies, one of the challenges is to distinguish functional mutations vital for cancer development, and filter out the unfunctional and random “passenger mutations.” In this study, we introduce a modified method to solve the so-called maximum weight submatrix problem which is based on two combinatorial properties, i.e., coverage and exclusivity. This problem can be used to find driver mutations. Particularly, we enhance an integrative model which combines mutation and expression data. We apply our method to simulated data, the experiment shows that our method is efficiency. Then we apply our proposed method onto real biological datasets, the results also show that it is applicable in real applications.
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Yan, C., Li, HT., Guo, AX., Sha, W., Zheng, CH. (2014). Simulated Annealing Based Algorithm for Mutated Driver Pathways Detecting. In: Huang, DS., Jo, KH., Wang, L. (eds) Intelligent Computing Methodologies. ICIC 2014. Lecture Notes in Computer Science(), vol 8589. Springer, Cham. https://doi.org/10.1007/978-3-319-09339-0_66
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DOI: https://doi.org/10.1007/978-3-319-09339-0_66
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09338-3
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