Browsing by Author "Liu, Baw-Juine"

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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
;
Liu, Baw-Juine
;
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.
Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data
(2006-07-01)
Tsou, Ann-Ping
;
Sun, Yi-Ming
;
Liu, Chia-Lin
;
Huang, Hsien-Da
;
Horng, Jorng-Tzong
Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.