کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6920793 864433 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Identification of mutated driver pathways in cancer using a multi-objective optimization model
ترجمه فارسی عنوان
شناسایی مسیرهای راننده جهش یافته در سرطان با استفاده از یک مدل بهینه سازی چند هدفه
کلمات کلیدی
مسیرهای راننده، مدل بهینه سازی چند هدفه الگوریتم ژنتیک، مدل یکپارچه، جهش راننده،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 72, 1 May 2016, Pages 22-29
نویسندگان
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