Browsing by Author "Wu, Li-Cheng"

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An expert system to predict protein thermostability using decision tree
(2009-07-01)
Wu, Li-Cheng
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Lee, Jian-Xin
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Huang, Hsien-Da
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Liu, Baw-Juine
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Horng, Jorng-Tzong
Protein thermostability information is closely linked to commercial production of many biomaterials. Recent developments have shown that amino acid composition, special sequence patterns and hydrogen bonds, disulfide bonds, salt bridges and so on are of considerable importance to thermostability. In this study, we present a system to integrate these various factors that predict protein thermostability. In this study, the features of proteins in the PGTdb are analyzed. We consider both structure and sequence features and correlation coefficients are incorporated into the feature selection algorithm. Machine learning algorithms are then used to develop identification systems and performances between the different algorithms are compared. In this research, two features, (E + F + M + R)/residue and charged/non-charged, are found to be critical to the thermostability of proteins. Although the sequence and structural models achieve a higher accuracy, sequence-only models provides sufficient accuracy for sequence-only thermostability prediction. (C) 2008 Elsevier Ltd. All rights reserved.
Database to dynamically aid probe design for virus identification
(2006-10-01)
Lin, Feng-Mao
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Huang, Hsien-Da
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Chang, Yu-Chung
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Tsou, Ann-Ping
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Chan, Pak-Leong
Viral infection poses a major problem for public health, horticulture, and animal husbandry, possibly causing severe health crises and economic losses. Viral infections can be identified by the specific detection of viral sequences in many ways. The microarray approach not only tolerates sequence variations of newly evolved virus strains, but can also simultaneously diagnose many viral sequences. Many chips have so far been designed for clinical use. Most are designed for special purposes, such as typing enterovirus infection, and compare fewer than 30 different viral sequences. None considers primer design, increasing the likelihood of cross hybridization to similar sequences from other viruses. To prevent this possibility, this work establishes a platform and database that provides users with specific probes of all known viral genome sequences to facilitate the design of diagnostic chips. This work develops a system for designing probes online. A user can select any number of different viruses and set the experimental conditions such as melting temperature and length of probe. The system then returns the optimal sequences from the database. We have also developed a heuristic algorithm to calculate the probe correctness and show the correctness of the algorithm.
Primer design for multiplex PCR using a genetic algorithm
(2007-07-01)
Wu, Li-Cheng
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Horng, Jorng-Tzong
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Huang, Hsi-Yuan
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Lin, Feng-Mao
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Huang, Hsien-Da
Multiplex Polymerase chain reaction (PCR) is the term used when more than one pair of primers is used in a polymerase chain reaction. The goal of multiplex PCR is to amplify several segments of target DNA simultaneously and thereby to conserve template DNA, save time, and minimize expense. The success of the experiment is dependent on primer design. However, this can be a dreary task as there are many constrains such as melting temperatures, primer length, GC content and complementarity that need to be optimized to obtain a good PCR product. In our investigations, we found few primer design tools for multiplex PCR and there was no suitable tool for our partners who want to use a multiplex PCR genotypic assay. The tool draws on a genetic algorithm where stochastic approaches based on the concept of biological evolution, biological genetics and genetic operations on chromosomes are used to find an optimal solution for multiplex PCR. The presented experimental results indicate that the proposed algorithm is able to find a set of primer pairs that not only obey the design properties but also work in the same tube.