Shih-Chieh Su - Academia.edu (original) (raw)
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Papers by Shih-Chieh Su
Proteome Science, 2013
Background: Proteins are essential biological molecules which play vital roles in nearly all biol... more Background: Proteins are essential biological molecules which play vital roles in nearly all biological processes. It is the tertiary structure of a protein that determines its functions. Therefore the prediction of a protein's tertiary structure based on its primary amino acid sequence has long been the most important and challenging subject in biochemistry, molecular biology and biophysics. In the past, the HP lattice model was one of the ab initio methods that many researchers used to forecast the protein structure. Although these kinds of simplified methods could not achieve high resolution, they provided a macrocosm-optimized protein structure. The model has been employed to investigate general principles of protein folding, and plays an important role in the prediction of protein structures. Methods: In this paper, we present an improved evolutionary algorithm for the protein folding problem. We study the problem on the 3D FCC lattice HP model which has been widely used in previous research. Our focus is to develop evolutionary algorithms (EA) which are robust, easy to implement and can handle various energy functions. We propose to combine three different local search methods, including lattice rotation for crossover, Ksite move for mutation, and generalized pull move; these form our key components to improve previous EA-based approaches. Results: We have carried out experiments over several data sets which were used in previous research. The results of the experiments show that our approach is able to find optimal conformations which were not found by previous EA-based approaches. Conclusions: We have investigated the geometric properties of the 3D FCC lattice and developed several local search techniques to improve traditional EA-based approaches to the protein folding problem. It is known that EA-based approaches are robust and can handle arbitrary energy functions. Our results further show that by extensive development of local searches, EA can also be very effective for finding optimal conformations on the 3D FCC HP model. Furthermore, the local searches developed in this paper can be integrated with other approaches such as the Monte Carlo and Tabu searches to improve their performance.
Lecture Notes in Computer Science, 2004
This paper presents a memetic algorithm with self-adaptive local search, applied to protein struc... more This paper presents a memetic algorithm with self-adaptive local search, applied to protein structure prediction in an HP, cubiclattice model. Besides describing in detail how the algorithm works, we report experimental results that justify important implementation choices, such as the introduction of speciation mechanisms and the extensive application of local search. Test runs on 48-mer chains show that the proposed algorithm has promising search capabilities.
Proteome Science, 2013
Background: Proteins are essential biological molecules which play vital roles in nearly all biol... more Background: Proteins are essential biological molecules which play vital roles in nearly all biological processes. It is the tertiary structure of a protein that determines its functions. Therefore the prediction of a protein's tertiary structure based on its primary amino acid sequence has long been the most important and challenging subject in biochemistry, molecular biology and biophysics. In the past, the HP lattice model was one of the ab initio methods that many researchers used to forecast the protein structure. Although these kinds of simplified methods could not achieve high resolution, they provided a macrocosm-optimized protein structure. The model has been employed to investigate general principles of protein folding, and plays an important role in the prediction of protein structures. Methods: In this paper, we present an improved evolutionary algorithm for the protein folding problem. We study the problem on the 3D FCC lattice HP model which has been widely used in previous research. Our focus is to develop evolutionary algorithms (EA) which are robust, easy to implement and can handle various energy functions. We propose to combine three different local search methods, including lattice rotation for crossover, Ksite move for mutation, and generalized pull move; these form our key components to improve previous EA-based approaches. Results: We have carried out experiments over several data sets which were used in previous research. The results of the experiments show that our approach is able to find optimal conformations which were not found by previous EA-based approaches. Conclusions: We have investigated the geometric properties of the 3D FCC lattice and developed several local search techniques to improve traditional EA-based approaches to the protein folding problem. It is known that EA-based approaches are robust and can handle arbitrary energy functions. Our results further show that by extensive development of local searches, EA can also be very effective for finding optimal conformations on the 3D FCC HP model. Furthermore, the local searches developed in this paper can be integrated with other approaches such as the Monte Carlo and Tabu searches to improve their performance.
Lecture Notes in Computer Science, 2004
This paper presents a memetic algorithm with self-adaptive local search, applied to protein struc... more This paper presents a memetic algorithm with self-adaptive local search, applied to protein structure prediction in an HP, cubiclattice model. Besides describing in detail how the algorithm works, we report experimental results that justify important implementation choices, such as the introduction of speciation mechanisms and the extensive application of local search. Test runs on 48-mer chains show that the proposed algorithm has promising search capabilities.