Biomedical subjects

Hung-Ming Chen

Publications and source records attributed to Hung-Ming Chen.

7 recordsLinked to original sources

PubMed2007

SODOCK: swarm optimization for highly flexible protein-ligand docking.

Protein-ligand docking can be formulated as a parameter optimization problem associated with an accurate scoring function, which aims to identify the translation, orientation, and conformation of a docked ligand with the lowest energy. The parameter optimization problem for highly flexible ligands with many rotatable bonds is more difficult than that for less flexible ligands using genetic algorithm (GA)-based approaches, due to the large numbers of parameters and high correlations among these parameters. This investigation presents a novel optimization algorithm SODOCK based on particle swarm optimization (PSO) for solving flexible protein-ligand docking problems. To improve efficiency and robustness of PSO, an efficient local search strategy is incorporated into SODOCK. The implementation of SODOCK adopts the environment and energy function of AutoDock 3.05. Computer simulation results reveal that SODOCK is superior to the Lamarckian genetic algorithm (LGA) of AutoDock, in terms of convergence performance, robustness, and obtained energy, especially for highly flexible ligands. The results also reveal that PSO is more suitable than the conventional GA in dealing with flexible docking problems with high correlations among parameters. This investigation also compared SODOCK with four state-of-the-art docking methods, namely GOLD 1.2, DOCK 4.0, FlexX 1.8, and LGA of AutoDock 3.05. SODOCK obtained the smallest RMSD in 19 of 37 cases. The average 2.29 A of the 37 RMSD values of SODOCK was better than those of other docking programs, which were all above 3.0 A.

Algorithms↗

PubMed2006

Accurate prediction of enzyme subfamily class using an adaptive fuzzy k-nearest neighbor method.

Amphiphilic pseudo-amino acid composition (Am-Pse-AAC) with extra sequence-order information is a useful feature for representing enzymes. This study first utilizes the k-nearest neighbor (k-NN) rule to analyze the distribution of enzymes in the Am-Pse-AAC feature space. This analysis indicates the distributions of multiple classes of enzymes are highly overlapped. To cope with the overlap problem, this study proposes an efficient non-parametric classifier for predicting enzyme subfamily class using an adaptive fuzzy r-nearest neighbor (AFK-NN) method, where k and a fuzzy strength parameter m are adaptively specified. The fuzzy membership values of a query sample Q are dynamically determined according to the position of Q and its weighted distances to the k nearest neighbors. Using the same enzymes of the oxidoreductases family for comparisons, the prediction accuracy of AFK-NN is 76.6%, which is better than those of Support Vector Machine (73.6%), the decision tree method C5.0 (75.4%) and the existing covariant-discriminate algorithm (70.6%) using a jackknife test. To evaluate the generalization ability of AFK-NN, the datasets for all six families of entirely sequenced enzymes are established from the newly updated SWISS-PROT and ENZYME database. The accuracy of AFK-NN on the new large-scale dataset of oxidoreductases family is 83.3%, and the mean accuracy of the six families is 92.1%.

Algorithms↗

PubMed2006

Interpretable gene expression classifier with an accurate and compact fuzzy rule base for microarray data analysis.

An accurate classifier with linguistic interpretability using a small number of relevant genes is beneficial to microarray data analysis and development of inexpensive diagnostic tests. Several frequently used techniques for designing classifiers of microarray data, such as support vector machine, neural networks, k-nearest neighbor, and logistic regression model, suffer from low interpretabilities. This paper proposes an interpretable gene expression classifier (named iGEC) with an accurate and compact fuzzy rule base for microarray data analysis. The design of iGEC has three objectives to be simultaneously optimized: maximal classification accuracy, minimal number of rules, and minimal number of used genes. An "intelligent" genetic algorithm IGA is used to efficiently solve the design problem with a large number of tuning parameters. The performance of iGEC is evaluated using eight commonly-used data sets. It is shown that iGEC has an accurate, concise, and interpretable rule base (1.1 rules per class) on average in terms of test classification accuracy (87.9%), rule number (3.9), and used gene number (5.0). Moreover, iGEC not only has better performance than the existing fuzzy rule-based classifier in terms of the above-mentioned objectives, but also is more accurate than some existing non-rule-based classifiers.

Algorithms↗

PubMed2004

Design of accurate classifiers with a compact fuzzy-rule base using an evolutionary scatter partition of feature space.

An evolutionary approach to designing accurate classifiers with a compact fuzzy-rule base using a scatter partition of feature space is proposed, in which all the elements of the fuzzy classifier design problem have been moved in parameters of a complex optimization problem. An intelligent genetic algorithm (IGA) is used to effectively solve the design problem of fuzzy classifiers with many tuning parameters. The merits of the proposed method are threefold: 1) the proposed method has high search ability to efficiently find fuzzy rule-based systems with high fitness values, 2) obtained fuzzy rules have high interpretability, and 3) obtained compact classifiers have high classification accuracy on unseen test patterns. The sensitivity of control parameters of the proposed method is empirically analyzed to show the robustness of the IGA-based method. The performance comparison and statistical analysis of experimental results using ten-fold cross validation show that the IGA-based method without heuristics is efficient in designing accurate and compact fuzzy classifiers using 11 well-known data sets with numerical attribute values.

Journal Article↗

PubMed2003

Urachal anomalies in children: experience at one institution.

BACKGROUND: The embryological and anatomical features of urachal anomalies have been well defined. Because of the variable clinical presentations, uniform guidelines for evaluation and treatment are lacking. In an attempt to establish an optimal diagnostic and treatment modality, we report our experience with urachal anomalies at a single institution over a 10-year period. METHODS: The records of 20 patients with urachal abnormalities were reviewed. These included 12 males and 8 females with ages from 1 day to 12 years (average, 3 years). The evaluation included symptoms and signs, and results of fistulography, sonography, and voiding cystography. Postoperative conditions were also reviewed. RESULTS: The presenting complaint was umbilical discharge in 14 patients, umbilical discharge with marked umbilical granulation tissue in 2, periumbilical erythema in 3, and abdominal pain in 1. Diagnostic evaluation included fistulography in 5 cases, sonography in 13, and voiding cystourethrography in 3. The 3 variants of urachal anomalies included a patent urachus in 4 patients (20%), urachal sinus in 13 (65%), and an infected urachal cyst in 3 (15%). Treatment consisted of primary excision with a cuff of the bladder in 3, excision with ligation in 1, excision of the sinus in 13, incision and drainage in 3, and secondary excision in 1. There was 1 postoperative wound infection. CONCLUSION: Diagnosis and treatment of urachal anomalies can be made with certainty if a good physical examination and proper imaging study are performed. Voiding urethrocystography might not be required in view of the fact that none of the patients studied had an associated urinary tract anomaly.

Child↗

PubMed2003

Antimicrobial susceptibility of common bacterial pathogens isolated from a new regional hospital in southern Taiwan.

BACKGROUND: Antimicrobial resistance has become a major health problem in Taiwan. While some trends in antimicrobial resistance are universal, others appear to be unique for specific regions. METHODS: To determine the distribution and antimicrobial drug resistance of bacterial pathogens in a new hospital in southern Taiwan, surveillance data on major bacterial pathogens isolated from Chang Gung Memorial Hospital at Chia-Yi from January 2002 through December 2002 were retrospectively analyzed. RESULTS: The most common gram-positive isolate was Staphylococcus aureus. Escherichia coli and Klebsiella pneumoniae were the two most common gram negative isolates. Pseudomonas aeruginosa ranked the first among gram-negative, glucose non-fermenting isolates, followed in the order of frequency by Acinetobacter baumannii. Oxacillin resistance rate of S. aureus was 58%, while vancomycin and teicoplanin remained effective against all of the isolates. The penicillin non-susceptibility rate of Streptococcus pneumoniae was 52%, and it is notable that the rate of resistance to erythromycin was 87%. Resistance to various antimicrobial agents for P. aeruginosa, Aeromonas hydrophila, and gram-negative enteric bacilli was very common in our study. Infections caused by multidrug-resistant A. baumannii was not uncommon in this hospital but fortunately, imipenem resistant A. baumannii was rarely encountered. Antimicrobial resistance was common in nontyphoid Salmonella, S. choleraesuis and serogroup B isolates in particular. CONCLUSION: The high rates of antimicrobial resistance among these major bacterial pathogens in this new hospital are impressive and alarming. Judicious use of antimicrobial agents can never be overemphasized. Continued surveillance of the changes of resistance patterns over time is necessary.

Drug Resistance, Bacterial↗

PubMed2002

Critical role of mitochondrial reactive oxygen species formation in visible laser irradiation-induced apoptosis in rat brain astrocytes (RBA-1).

Laser irradiation-induced phototoxicity has been intensively applied in clinical photodynamic therapy for the treatment of a variety of tumors. However, the precise laser damage sites as well as the underlying mechanisms at the subcellular level are unknown. Using a mitochondrial fluorescent marker, MitoTracker Green, severe mitochondrial swelling was noted in laser-irradiated rat brain astrocytes. Nucleus condensation and fragmentation revealed by propidium iodide nucleic acid staining indicated that laser-irradiated cells died from apoptosis. Using an intracellular reactive oxygen species (ROS) fluorescent dye, 2',7'-dichlorofluorescin diacetate, heterogeneous distribution of ROS inside astrocytes was observed after laser irradiation. The level of ROS in the mitochondrial compartment was found to be higher than in other parts of the cell. With another ROS fluorescent dye, dihydrorhodamine-123, and time-lapse laser scanning confocal microscopy, a substantial increase in mitochondrial ROS (mROS) was visualized in visible laser-irradiated astrocytes. The antioxidants melatonin and vitamin E largely attenuated laser irradiation-induced mROS formation and prevented apoptosis. Cyclosporin A (CsA), a mitochondrial permeability transition (MPT) blocker, did not prevent visible laser irradiation-induced mROS formation and apoptosis. In conclusion, mROS formation contributes significantly to visible laser irradiation-induced apoptosis via an MPT-independent pathway.

Aldehydes↗