Browsing by Author "Chang, Wen-Chi"

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dbPTM 3.0: an informative resource for investigating substrate site specificity and functional association of protein post-translational modifications
(2013-01-01)
Lu, Cheng-Tsung
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Huang, Kai-Yao
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Su, Min-Gang
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Lee, Tzong-Yi
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Bretana, Neil Arvin
Protein modification is an extremely important post-translational regulation that adjusts the physical and chemical properties, conformation, stability and activity of a protein; thus altering protein function. Due to the high throughput of mass spectrometry (MS)-based methods in identifying site-specific post-translational modifications (PTMs), dbPTM (http://dbPTM.mbc.nctu.edu.tw/) is updated to integrate experimental PTMs obtained from public resources as well as manually curated MS/MS peptides associated with PTMs from research articles. Version 3.0 of dbPTM aims to be an informative resource for investigating the substrate specificity of PTM sites and functional association of PTMs between substrates and their interacting proteins. In order to investigate the substrate specificity for modification sites, a newly developed statistical method has been applied to identify the significant substrate motifs for each type of PTMs containing sufficient experimental data. According to the data statistics in dbPTM, > 60% of PTM sites are located in the functional domains of proteins. It is known that most PTMs can create binding sites for specific protein-interaction domains that work together for cellular function. Thus, this update integrates protein-protein interaction and domain-domain interaction to determine the functional association of PTM sites located in protein-interacting domains. Additionally, the information of structural topologies on transmembrane (TM) proteins is integrated in dbPTM in order to delineate the structural correlation between the reported PTM sites and TM topologies. To facilitate the investigation of PTMs on TM proteins, the PTM substrate sites and the structural topology are graphically represented. Also, literature information related to PTMs, orthologous conservations and substrate motifs of PTMs are also provided in the resource. Finally, this version features an improved web interface to facilitate convenient access to the resource.
FMM: a web server for metabolic pathway reconstruction and comparative analysis
(2009-07-01)
Chou, Chih-Hung
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Chang, Wen-Chi
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Chiu, Chih-Min
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Huang, Chih-Chang
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Huang, Hsien-Da
Synthetic Biology, a multidisciplinary field, is growing rapidly. Improving the understanding of biological systems through mimicry and producing bio-orthogonal systems with new functions are two complementary pursuits in this field. A web server called FMM (From Metabolite to Metabolite) was developed for this purpose. FMM can reconstruct metabolic pathways form one metabolite to another metabolite among different species, based mainly on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and other integrated biological databases. Novel presentation for connecting different KEGG maps is newly provided. Both local and global graphical views of the metabolic pathways are designed. FMM has many applications in Synthetic Biology and Metabolic Engineering. For example, the reconstruction of metabolic pathways to produce valuable metabolites or secondary metabolites in bacteria or yeast is a promising strategy for drug production. FMM provides a highly effective way to elucidate the genes from which species should be cloned into those microorganisms based on FMM pathway comparative analysis. Consequently, FMM is an effective tool for applications in synthetic biology to produce both drugs and biofuels. This novel and innovative resource is now freely available at http://FMM.mbc.nctu.edu.tw/.
Geometric Integration of Heterogeneous Models for Multisatellite Image Positioning
(2012-07-01)
Chen, Liang-Chien
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Chang, Wen-Chi
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Teo, Tee-Ann
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土木工程學系
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Department of Civil Engineering
With the wider availability of more and more images acquired from various satellites, the integration of different orientation models for different sensors has become an important task in order to maintain geometrical consistency. This study combines two heterogeneous geometric correction models, namely, direct georeferencing and the rational function model for multi-satellite image positioning. Two types of adjustment models, collocation-based block adjustment (CBBA) and collocation-aided block adjustment (CABA), are proposed to reach the goal. The former is based on the concept that the adjustment is first performed on individual images, and then, all images are integrated. Discrepancies are compensated for by least squares collocation (LSC). The latter method entails simultaneous adjustment of the two heterogeneous models followed by LSC. Experimental results indicate that the proposed method can significantly improve the geometric accuracy as well as reduce geometric discrepancies between images. We also demonstrate that CABA is slightly better than CBBA.
GPMiner: an integrated system for mining combinatorial cis-regulatory elements in mammalian gene group
(2012-01-17)
Lee, Tzong-Yi
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Chang, Wen-Chi
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Hsu, Justin Bo-Kai
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Chang, Tzu-Hao
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Shien, Dray-Ming
Background: Sequence features in promoter regions are involved in regulating gene transcription initiation. Although numerous computational methods have been developed for predicting transcriptional start sites (TSSs) or transcription factor (TF) binding sites (TFBSs), they lack annotations for do not consider some important regulatory features such as CpG islands, tandem repeats, the TATA box, CCAAT box, GC box, over-represented oligonucleotides, DNA stability, and GC content. Additionally, the combinatorial interaction of TFs regulates the gene group that is associated with same expression pattern. To investigate gene transcriptional regulation, an integrated system that annotates regulatory features in a promoter sequence and detects co-regulation of TFs in a group of genes is needed. Results: This work identifies TSSs and regulatory features in a promoter sequence, and recognizes co-occurrence of cis-regulatory elements in co-expressed genes using a novel system. Three well-known TSS prediction tools are incorporated with orthologous conserved features, such as CpG islands, nucleotide composition, over-represented hexamer nucleotides, and DNA stability, to construct the novel Gene Promoter Miner (GPMiner) using a support vector machine (SVM). According to five-fold cross-validation results, the predictive sensitivity and specificity are both roughly 80%. The proposed system allows users to input a group of gene names/symbols, enabling the co-occurrence of TFBSs to be determined. Additionally, an input sequence can also be analyzed for homogeneity of experimental mammalian promoter sequences, and conserved regulatory features between homologous promoters can be observed through cross-species analysis. After identifying promoter regions, regulatory features are visualized graphically to facilitate gene promoter observations. Conclusions: The GPMiner, which has a user-friendly input/output interface, has numerous benefits in analyzing human and mouse promoters. The proposed system is freely available at http://GPMiner.mbc.nctu.edu.tw/.
Identifying transcriptional start sites of human microRNAs based on high-throughput sequencing data
(2011-11-01)
Chien, Chia-Hung
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Sun, Yi-Ming
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Chang, Wen-Chi
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Chiang-Hsieh, Pei-Yun
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Lee, Tzong-Yi
MicroRNAs (miRNAs) are critical small non-coding RNAs that regulate gene expression by hybridizing to the 3'-untranslated regions (3'-UTR) of target mRNAs, subsequently controlling diverse biological processes at post-transcriptional level. How miRNA genes are regulated receives considerable attention because it directly affects miRNA-mediated gene regulatory networks. Although numerous prediction models were developed for identifying miRNA promoters or transcriptional start sites (TSSs), most of them lack experimental validation and are inadequate to elucidate relationships between miRNA genes and transcription factors (TFs). Here, we integrate three experimental datasets, including cap analysis of gene expression (CAGE) tags, TSS Seq libraries and H3K4me3 chromatin signature derived from high-throughput sequencing analysis of gene initiation, to provide direct evidence of miRNA TSSs, thus establishing an experimental-based resource of human miRNA TSSs, named miRStart. Moreover, a machine-learning-based Support Vector Machine (SVM) model is developed to systematically identify representative TSSs for each miRNA gene. Finally, to demonstrate the effectiveness of the proposed resource, an important human intergenic miRNA, hsa-miR-122, is selected to experimentally validate putative TSS owing to its high expression in a normal liver. In conclusion, this work successfully identified 847 human miRNA TSSs (292 of them are clustered to 70 TSSs of miRNA clusters) based on the utilization of high-throughput sequencing data from TSS-relevant experiments, and establish a valuable resource for biologists in advanced research in miRNA-mediated regulatory networks.
Incorporating Structural Characteristics for Identification of Protein Methylation Sites
(2009-07-15)
Shien, Dray-Ming
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Lee, Tzong-Yi
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Chang, Wen-Chi
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Hsu, Justin Bo-Kai
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Horng, Jorng-Tzong
Studies over the last few years have identified protein methylation on histones and other proteins that are involved in the regulation of gene transcription. Several works have developed approaches to identify computationally the potential methylation sites on lysine and arginine. Studies of protein tertiary structure have demonstrated that the sites of protein methylation are preferentially in regions that are easily accessible. However, previous studies have not taken into account the solvent-accessible surface area (ASA) that surrounds the methylation sites. This work presents a method named MASA that combines the support vector machine with the sequence and structural characteristics of proteins to identify methylation sites on lysine, arginine, glutamate, and asparagine. Since most experimental methylation sites are not associated with corresponding protein tertiary structures in the Protein Data Bank, the effective solvent-accessible prediction tools have been adopted to determine the potential ASA values of amino acids in proteins. Evaluation of predictive performance by cross-validation indicates that the ASA values around the methylation sites can improve the accuracy of prediction. Additionally, an independent test reveals that the prediction accuracies for methylated lysine and arginine are 80.8 and 85.0%, respectively. Finally, the proposed method is implemented as an effective system for identifying protein methylation sites. The developed web server is freely available at http:/IMASA.mbc.nctu.edu.tw/. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 30: 1532-1543, 2009
Incorporating Support Vector Machine for Identifying Protein Tyrosine Sulfation Sites
(2009-11-30)
Chang, Wen-Chi
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Lee, Tzong-Yi
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Shien, Dray-Ming
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Hsu, Justin Bo-Kai
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Horng, Jorng-Tzong
Tyrosine sulfation is a post-translational modification of many secreted and membrane-bound proteins. It governs protein-protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty-two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five-fold cross-validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in fivefold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 30: 2526-2537, 2009
Large-Scale Investigation of Human TF-miRNA Relations Based on Coexpression Profiles
(2014)
Chien, Chia-Hung
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Chiang-Hsieh, Yi-Fan
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Tsou, Ann-Ping
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Weng, Shun-Long
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Chang, Wen-Chi
Noncoding, endogenous microRNAs (miRNAs) are fairly well known for regulating gene expression rather than protein coding. Dysregulation of miRNA gene, either upregulated or downregulated, may lead to severe diseases or oncogenesis, especially when the miRNA disorder involves significant bioreactions or pathways. Thus, how miRNA genes are transcriptionally regulated has been highlighted as well as target recognition in recent years. In this study, a large-scale investigation of novel cis- and trans-elements was undertaken to further determine TF-miRNA regulatory relations, which are necessary to unravel the transcriptional regulation of miRNA genes. Based on miRNA and annotated gene expression profiles, the term "coTFBS" was introduced to detect common transcription factors and the corresponding binding sites within the promoter regions of each miRNA and its coexpressed annotated genes. The computational pipeline was successfully established to filter redundancy due to short sequencemotifs for TFBS pattern search. Eventually, we identified more convinced TF-miRNA regulatory relations for 225 human miRNAs. This valuable information is helpful in understanding miRNA functions and provides knowledge to evaluate the therapeutic potential in clinical research. Once most expression profiles of miRNAs in the latest database are completed, TF candidates of more miRNAs can be explored by this filtering approach in the future.
miRExpress: Analyzing high-throughput sequencing data for profiling microRNA expression
(2009-10-12)
Wang, Wei-Chi
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Lin, Feng-Mao
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Chang, Wen-Chi
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Lin, Kuan-Yu
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Huang, Hsien-Da
Background: MicroRNAs (miRNAs), small non-coding RNAs of 19 to 25 nt, play important roles in gene regulation in both animals and plants. In the last few years, the oligonucleotide microarray is one high-throughput and robust method for detecting miRNA expression. However, the approach is restricted to detecting the expression of known miRNAs. Second-generation sequencing is an inexpensive and high-throughput sequencing method. This new method is a promising tool with high sensitivity and specificity and can be used to measure the abundance of small-RNA sequences in a sample. Hence, the expression profiling of miRNAs can involve use of sequencing rather than an oligonucleotide array. Additionally, this method can be adopted to discover novel miRNAs. Results: This work presents a systematic approach, miRExpress, for extracting miRNA expression profiles from sequencing reads obtained by second-generation sequencing technology. A stand-alone software package is implemented for generating miRNA expression profiles from high-throughput sequencing of RNA without the need for sequenced genomes. The software is also a database-supported, efficient and flexible tool for investigating miRNA regulation. Moreover, we demonstrate the utility of miRExpress in extracting miRNA expression profiles from two Illumina data sets constructed for the human and a plant species. Conclusion: We develop miRExpress, which is a database-supported, efficient and flexible tool for detecting miRNA expression profile. The analysis of two Illumina data sets constructed from human and plant demonstrate the effectiveness of miRExpress to obtain miRNA expression profiles and show the usability in finding novel miRNAs.
N-Ace: Using Solvent Accessibility and Physicochemical Properties to Identify Protein N-Acetylation Sites
(2010-11-30)
Lee, Tzong-Yi
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Hsu, Justin Bo-Kai
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Lin, Feng-Mao
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Chang, Wen-Chi
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Hsu, Po-Chiang
Protein acetylation, which is catalyzed by acetyltransferases, is a type of post-translational modification and crucial to numerous essential biological processes, including transcriptional regulation, apoptosis, and cytokine signaling. As the experimental identification of protein acetylation sites is time consuming and laboratory intensive, several computational approaches have been developed for identifying the candidates of experimental validation. In this work, solvent accessibility and the physicochemical properties of proteins are utilized to identify acetylated alanine, glycine, lysine, methionine, serine, and threonine. A two-stage support vector machine was applied to learn the computational models with combinations of amino acid sequences, and the accessible surface area and physicochemical properties of proteins. The predictive accuracy thus achieved is 5% to 14% higher than that of models trained using only amino acid sequences. Additionally, the substrate specificity of the acetylated site was investigated in detail with reference to the subcellular colocalization of acetyltransferases and acetylated proteins. The proposed method, N-Ace, is evaluated using independent test sets in various acetylated residues and predictive accuracies of 90% were achieved, indicating that the performance of N-Ace is comparable with that of other acetylation prediction methods. N-Ace not only provides a user-friendly input/output interface but also is a creative method for predicting protein acetylation sites. This novel analytical resource is now freely available at http://N-Ace.mbc.NCTU.edu.tw/. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 31: 2759-2771, 2010
N-Ace: Using Solvent Accessibility and Physicochemical Properties to Identify Protein N-Acetylation Sites
(2010-11-30)
Lee, Tzong-Yi
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Hsu, Justin Bo-Kai
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Lin, Feng-Mao
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Chang, Wen-Chi
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Hsu, Po-Chiang
Protein acetylation, which is catalyzed by acetyltransferases, is a type of post-translational modification and crucial to numerous essential biological processes, including transcriptional regulation, apoptosis, and cytokine signaling. As the experimental identification of protein acetylation sites is time consuming and laboratory intensive, several computational approaches have been developed for identifying the candidates of experimental validation. In this work, solvent accessibility and the physicochemical properties of proteins are utilized to identify acetylated alanine, glycine, lysine, methionine, serine, and threonine. A two-stage support vector machine was applied to learn the computational models with combinations of amino acid sequences, and the accessible surface area and physicochemical properties of proteins. The predictive accuracy thus achieved is 5% to 14% higher than that of models trained using only amino acid sequences. Additionally, the substrate specificity of the acetylated site was investigated in detail with reference to the subcellular colocalization of acetyltransferases and acetylated proteins. The proposed method, N-Ace, is evaluated using independent test sets in various acetylated residues and predictive accuracies of 90% were achieved, indicating that the performance of N-Ace is comparable with that of other acetylation prediction methods. N-Ace not only provides a user-friendly input/output interface but also is a creative method for predicting protein acetylation sites. This novel analytical resource is now freely available at http://N-Ace.mbc.NCTU.edu.tw/. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 31: 2759-2771, 2010
Phosphor Conformal Coating by a Novel Spray Method for White Light-emitting Diodes as Applied to Liquid-crystal Backlight Module
(2009)
Huang, Hsin-Tao
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Tsai, Chuang-Chuang
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Huang, Yi-Pai
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Chen, Jerry
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Lin, Jeremy
This work presents a novel pulsed spray process (PSP) for the conformal coating of yellow YAG:Ce(3+) phosphor on blue InGaN-based light emitting diodes (LEDs) for TFT-LCD backlight applications. This new approach exhibits much greater color spatial uniformity than conventional white LEDs coated with YAG phosphor by dispensing method. Unlike conformal coating by electrophorestic deposition (EPD), this new phosphor coating scheme of PSP represents an environmental friendly solution without Cr ion pollution. Additionally. PSP can be combined with an array blue chips on board (COB) in a manner that is compatible with large-area processing with high manufacture throughput, and can reduce the costs of TFT-LCD backlight applications.
PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants
(2016-01-04)
Chow, Chi-Nga
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Zheng, Han-Qin
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Wu, Nai-Yun
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Chien, Chia-Hung
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Huang, Hsien-Da
Transcription factors (TFs) are sequence-specific DNA-binding proteins acting as critical regulators of gene expression. The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN2.itps.ncku.edu.tw) provides an informative resource for detecting transcription factor binding sites (TFBSs), corresponding TFs, and other important regulatory elements (CpG islands and tandem repeats) in a promoter or a set of plant promoters. Additionally, TFBSs, CpG islands, and tandem repeats in the conserve regions between similar gene promoters are also identified. The current PlantPANrelease (version 2.0) contains 16 960 TFs and 1143 TF binding site matrices among 76 plant species. In addition to updating of the annotation information, adding experimentally verified TF matrices, and making improvements in the visualization of transcriptional regulatory networks, several new features and functions are incorporated. These features include: (i) comprehensive curation of TF information (response conditions, target genes, and sequence logos of binding motifs, etc.), (ii) co-expression profiles of TFs and their target genes under various conditions, (iii) protein-protein interactions among TFs and their co-factors, (iv) TFtarget networks, and (v) downstream promoter elements. Furthermore, a dynamic transcriptional regulatory network under various conditions is provided in PlantPAN 2.0. The PlantPAN 2.0 is a systematic platform for plant promoter analysis and reconstructing transcriptional regulatory networks.
RegPhos: a system to explore the protein kinase-substrate phosphorylation network in humans
(2011-01-01)
Lee, Tzong-Yi
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Hsu, Justin Bo-Kai
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Chang, Wen-Chi
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Huang, Hsien-Da
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生物科技學系
Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. With the increasing number of experimental phosphorylation sites that has been identified by mass spectrometry-based proteomics, the desire to explore the networks of protein kinases and substrates is motivated. Manning et al. have identified 518 human kinase genes, which provide a starting point for comprehensive analysis of protein phosphorylation networks. In this study, a knowledgebase is developed to integrate experimentally verified protein phosphorylation data and protein-protein interaction data for constructing the protein kinase-substrate phosphorylation networks in human. A total of 21 110 experimental verified phosphorylation sites within 5092 human proteins are collected. However, only 4138 phosphorylation sites (similar to 20%) have the annotation of catalytic kinases from public domain. In order to fully investigate how protein kinases regulate the intracellular processes, a published kinase-specific phosphorylation site prediction tool, named KinasePhos is incorporated for assigning the potential kinase. The web-based system, RegPhos, can let users input a group of human proteins; consequently, the phosphorylation network associated with the protein subcellular localization can be explored. Additionally, time-coursed microarray expression data is subsequently used to represent the degree of similarity in the expression profiles of network members. A case study demonstrates that the proposed scheme not only identify the correct network of insulin signaling but also detect a novel signaling pathway that may cross-talk with insulin signaling network. This effective system is now freely available at http://RegPhos.mbc.nctu.edu.tw.
Visible-Light Modulation on Lattice Dielectric Responses of a Piezo-Phototronic Soft Material
(2015-12-16)
Huang, E-Wen
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Hsu, Yu-Hsiang
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Chuang, Wei-Tsung
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Ko, Wen-Ching
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Chang, Chung-Kai