A Review: Applying Genetic Algorithms for Motif Discovery
نویسندگان
چکیده
This paper explores & reviews the use of genetic algorithms by various researchers as a solution to discover motifs in molecular sequences. This survey talks about the general GA based procedure for motif discovery & reviews the latest developments in DNA motif finding using Genetic algorithms. Although GA approach has not been applied extensively by researchers as compared to other computational methods for motif discovery, however in the recent past many researchers have explored the usefulness of GA for finding motifs in sequences. This paper is an attempt towards exploring the effectiveness of GA based approach for motif discovery.
منابع مشابه
Development of an Efficient Hybrid Method for Motif Discovery in DNA Sequences
This work presents a hybrid method for motif discovery in DNA sequences. The proposed method called SPSO-Lk, borrows the concept of Chebyshev polynomials and uses the stochastic local search to improve the performance of the basic PSO algorithm as a motif finder. The Chebyshev polynomial concept encourages us to use a linear combination of previously discovered velocities beyond that proposed b...
متن کاملLimitations and potentials of current motif discovery algorithms
Computational methods for de novo identification of gene regulation elements, such as transcription factor binding sites, have proved to be useful for deciphering genetic regulatory networks. However, despite the availability of a large number of algorithms, their strengths and weaknesses are not sufficiently understood. Here, we designed a comprehensive set of performance measures and benchmar...
متن کاملThe Introduction of a Heuristic Mutation Operator to Strengthen the Discovery Component of XCS
The extended classifier systems (XCS) by producing a set of rules is (classifier) trying to solve learning problems as online. XCS is a rather complex combination of genetic algorithm and reinforcement learning that using genetic algorithm tries to discover the encouraging rules and value them by reinforcement learning. Among the important factors in the performance of XCS is the possibility to...
متن کاملThe Introduction of a Heuristic Mutation Operator to Strengthen the Discovery Component of XCS
The extended classifier systems (XCS) by producing a set of rules is (classifier) trying to solve learning problems as online. XCS is a rather complex combination of genetic algorithm and reinforcement learning that using genetic algorithm tries to discover the encouraging rules and value them by reinforcement learning. Among the important factors in the performance of XCS is the possibility to...
متن کاملConstrained Motif Discovery
The goal of motif discovery algorithms is to efficiently find unknown recurring patterns in time series. Most available algorithms cannot utilize domain knowledge in any way which results in quadratic or at least sub-quadratic time and space complexity. For large time series datasets for which domain knowledge can be available this is a severe limitation. In this paper we define the Constrained...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012