An Efficient Exact Method For Identifying Mutated Driver Pathways in Cancer

One of the key challenges in bioinformatics is to find the distinction between driver mutations that lead to tumorigenesis and random passenger mutations, which are known to be neutral and does not play any role in cancer development. To solve this problem, several approaches and techniques were used. In this article, we introduce an algorithm based on an exact approach in order to solve the so called “maximum weight submatrix problem”. The proposed algorithm maximizes the weight and samples all the possible pathways that can be found. We present the details about our algorithm and then compare them to a metaheuristic algorithm called Genetic Algorithm (GA) and with another exact model named Binary Linear Programming (BLP). Our Exact Algorithm shows good results in terms of maximizing the weight and finding all possible pathways.