Cheng-Huei Yang

A hybrid feature selection method for DNA microarray data

Gene expression profiles, which represent the state of a cell at a molecular level, have great potential as a medical diagnosis tool. In cancer classification, available training data sets are generally of a fairly small sample size compared to the number of genes involved. Along with training data limitations, this constitutes a challenge to certain classification methods. Feature (gene) selection can be used to successfully extract those genes that directly influence classification accuracy and to eliminate genes which have no influence on it. This significantly improves calculation performance and classification accuracy. In this paper, correlation-based feature selection (CFS) and the Taguchi-genetic algorithm (TGA) method were combined into a hybrid method, and the K-nearest neighbor (KNN) with the leave-one-out cross-validation (LOOCV) method served as a classifier for eleven classification profiles to calculate the classification accuracy. Experimental results show that the proposed method reduced redundant features effectively and achieved superior classification accuracy. The classification accuracy obtained by the proposed method was higher in ten out of the eleven gene expression data set test problems when compared to other classification methods from the literature.

An improved particle swarm optimization with double-bottom chaotic maps for numerical optimization

Chaos theory studies the behavior of dynamical systems that are highly sensitive to their initial conditions. This effect is popularly referred to as the butterfly effect. Small differences in the initial conditions yield widely diverging outcomes for chaotic systems, rendering long-term prediction impossible in general. In mathematics, a chaotic map is a map (i.e., an evolution function) that exhibits some sort of chaotic behavior. Chaotic maps occur in the study of dynamical systems and often generate fractals. In this paper, an improved logistic map, namely a double-bottom map, with particle swarm optimization was applied to the test function. Simple PSO adopts a random sequence with a random starting point as a parameter, and relies on this parameter to update the positions and velocities of the particles. However, PSO often leads to premature convergence, especially in complex multi-peak search problems. In recent years, the use of chaotic sequences in optimization techniques rather than random sequences with random seeds has been growing steadily. Chaotic sequences, which are created by means of chaotic maps, have been proven easy and fast to generate and are more easily stored then random seed processes. They can improve the performance of PSO due to their unpredictability. Double-bottom maps are designed by the updating equation of PSO in order to balance the exploration and exploitation capability. We embedded many commonly used chaotic maps as well as our double-bottom map into PSO to improve performance, and compared these versions to each other to demonstrate the effectiveness of the PSO with the double-bottom map. We call this improved PSO method Double-Bottom Map PSO (DBMPSO). In the conducted experiments, PSO, DBMPSO and other chaotic PSOs were extensively compared on 22 benchmark test functions. The experimental results indicate that the performance of DBMPSO is significantly better than the performance of other PSOs tested.

Operon Prediction Using Chaos Embedded Particle Swarm Optimization

Operons contain valuable information for drug design and determining protein functions. Genes within an operon are co-transcribed to a single-strand mRNA and must be coregulated. The identification of operons is, thus, critical for a detailed understanding of the gene regulations. However, currently used experimental methods for operon detection are generally difficult to implement and time consuming. In this paper, we propose a chaotic binary particle swarm optimization (CBPSO) to predict operons in bacterial genomes. The intergenic distance, participation in the same metabolic pathway and the cluster of orthologous groups (COG) properties of the Escherichia coli genome are used to design a fitness function. Furthermore, the Bacillus subtilis, Pseudomonas aeruginosa PA01, Staphylococcus aureus and Mycobacterium tuberculosis genomes are tested and evaluated for accuracy, sensitivity, and specificity. The computational results indicate that the proposed method works effectively in terms of enhancing the performance of the operon prediction. The proposed method also achieved a good balance between sensitivity and specificity when compared to methods from the literature.

Mutagenic Primer Design for Mismatch PCR-RFLP SNP Genotyping Using a Genetic Algorithm

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) is useful in small-scale basic research studies of complex genetic diseases that are associated with single nucleotide polymorphism (SNP). Designing a feasible primer pair is an important work before performing PCR-RFLP for SNP genotyping. However, in many cases, restriction enzymes to discriminate the target SNP resulting in the primer design is not applicable. A mutagenic primer is introduced to solve this problem. GA-based Mismatch PCR-RFLP Primers Design (GAMPD) provides a method that uses a genetic algorithm to search for optimal mutagenic primers and available restriction enzymes from REBASE. In order to improve the efficiency of the proposed method, a mutagenic matrix is employed to judge whether a hypothetical mutagenic primer can discriminate the target SNP by digestion with available restriction enzymes. The available restriction enzymes for the target SNP are mined by the updated core of SNP-RFLPing. GAMPD has been used to simulate the SNPs in the human SLC6A4 gene under different parameter settings and compared with SNP Cutter for mismatch PCR-RFLP primer design. The in silico simulation of the proposed GAMPD program showed that it designs mismatch PCR-RFLP primers. The GAMPD program is implemented in JAVA and is freely available at http://bio.kuas.edu.tw/gampd/.

Associate PCR-RFLP Assay Design With SNPs Based on Genetic Algorithm in Appropriate Parameters Estimation

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) is a commonly used laboratory technique and useful in small-scale basic research studies of complex genetic diseases that are associated with single nucleotide polymorphisms (SNPs). Before PCR-RFLP assay for SNP genotyping can be performed, a feasible primer pair observes numerous constraints and an available restriction enzyme for discriminating a target SNP, are required. The computation of feasible PCR-RFLP primers and find available restriction enzymes simultaneously aim at a target SNP is a challenging problem. Here, we propose an available method which combines the updated core of SNP-RFLPing with a genetic algorithm to reliably mine available restriction enzymes and search for feasible PCR-RFLP primers. We have in silico simulated the method in the SLC6A4 gene under different parameter settings and provided an appropriate parameter setting. The wet laboratory validation showed that it indeed usable in providing the available restriction enzymes and designing feasible primers that fit the common primer constraints. We have provided an easy and kindly interface to assist the researchers designing their PCR-RFLP assay for SNP genotyping. The program is implemented in JAVA and is freely available at http://bio.kuas.edu.tw/ganpd/.

CpGPAP: CpG island predictor analysis platform

BackgroundGenomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).ResultsCpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at http://bio.kuas.edu.tw/CpGPAP/.ConclusionsThe platforms supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.

Environmental Control Aid System for People with Physical Disabilities

Assistive technology (AT) is becoming increasingly important for improving the mobility and language learning capabilities of persons with disabilities, thus enabling them to function independently and to improve their social opportunities. The Morse code has been shown to be a valuable tool in assistive technology, augmentative and alternative communication, and rehabilitation for people with neuromuscular diseases such as amyotrophic lateral sclerosis, multiple sclerosis, and muscular dystrophy. In this paper, we designed and implemented a wireless environmental control aid system using the Morse code as an adapted access communication tool, which includes three types of switch: single-switch, double-switch, and six-switch types. People with disabilities can easily control all types of electronic appliance without restrictions owing to spatial arrangements using a signal transmission based on radio frequency (RF). Experimental results revealed that three participants with disabilities were able to gain access to electronic facilities after six weeks of practice with the new system.

An internet access device for physically impaired users of Chanjei morse code

Abstract Due to the rapid growth of Internet resources and technology, Internet access has become an important method of accessing and retrieving information. However, for some physically handicapped persons whose hand coordination and dexterity are impaired by such ailments as muscle atrophy, cerebral palsy, or other severe handicaps, the use of a conventional keyboard or similar standard input devices is not an option. Therefore, we designed and implemented, in this study, an easy‐to‐operate input interface, which was specifically designed for physically disabled Mandarin users to facilitate access to the Internet for them. Morse code, with an easily operated 1/2/6‐switch input device, was selected as an adaptive communication tool. The experimental results show that three physically impaired users could easily gain access to the Internet after three weeks’ practice on this proposed system.

IMPROVED MEASUREMENT OF GRIP STRENGTH THROUGH USE OF A PRESSURE SENSITIVE HAND DYNAMOMETER

Computers play an increasingly important role in daily lives due to rapid developments in information and computer technology. Computers as instruments for physical rehabilitation are becoming more and more prominent. This paper introduces an improved measurement of grip strength through use of a pressure sensitive hand dynamometer. This system can reliably assess a users grip strength through recording sudden changes in load cell sensors using a circuit and A/D adapter. The analyzed data is directly displayed on an LCD (Liquid Crystal Display) or is transformed and saved in a data record file via a PC interface. The compiled data can be combined with a patients case history and stored in a database as future reference for clinical use. The system is more efficient, cheaper to operate and more convenient to use than comparable systems currently used by doctors to monitor and analyze the progress of a patients individually designed rehabilitation program.

An intelligent Chinese phonetic on-screen virtual keyboard system

In this paper, we designed and implemented a user-friendly Chinese phonetic on-screen virtual keyboard key-in system for persons with disabilities. The proposed system inputs the Chinese characters by way of the mouse selecting phonetic symbols. After selecting the initial phonetic symbol, a list of possible phonetic symbol combinations is shown. The proposed system can decrease the number of input clicks needed to select a character, thereby improving typing speed. In addition, the size of the keyboard can be adjusted to increase accuracy and convenience. The system also provides temporary saving and scanning of selections, which makes the keyboard convenient for users. The most frequently typed characters typed by an individual user will be ranked first and this ranking constantly adjusted to facilitate character selection. Moreover, the proposed system shows common combinations of the character typed with other Chinese characters. The system will list all of the possible term correlations for a user to choose from, so that the user spends considerably less time inputting frequently used character combinations. Experimental results showed that the proposed on-screen virtual keyboard system provides an operation interface, which is easier to use, and achieves faster typing speeds compared to two other systems tested.