Browsing by Author "Horng, JT"

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A computational approach to discover differential cooperation of regulatory sites in functionally related genes in yeast genome
(2004-11-01)
Huang, HD
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Horng, JT
;
Chang, CH
;
Tsou, TS
;
Hong, JY
The availability of genome-wide gene expression data provides a unique set of genes from which to decipher the mechanisms underlying the common transcriptional response. A set of transcription factors which bind to target sites regulate the gene transcription cooperatively. This motivates us to discover the site associations of known transcription factor binding sites and certain repetitive elements. Those over-represented repetitive elements in the promoter regions of functionally related genes are predicted as putative regulatory elements. The study is to analyze how the differential site associations of the known regulatory sites and putative regulatory elements are distributed in the promoter regions of groups of functionally related genes. The functional-specific site associations are discovered by a statistical approach and the over-represented repetitive elements involving in the site associations are possible to be transcription factor binding sites. The site associations facilitate to predict functional-specific putative regulatory elements and to identify genes potentially co-regulated by the putative regulatory elements. Our proposed approach is applied to Saccharomyces cerevisiae and the promoter regions of yeast ORFs.
An agent-based system to discover protein-protein interactions, identify protein complexes and proteins with multiple peptide mass fingerprints
(2006-07-15)
Lee, TY
;
Horng, JT
;
Juan, HF
;
Huang, HD
;
Wu, LC
Proteins "work together" by actually binding to form multicomponent complexes that carry out specific functions. Proteomic analyses based on the mass spectrum are now key methods to determine the components in protein complexes. The protein-protein interaction or functional association may be known to exist among the extracted protein spots while analyzing the proteins on the 2D gel. In this study, we develop an agent-based system, namely AgentMultiProtIdent, which integrated two protein identification tools and a variety of databases storing relations among proteins and used to discover protein-protein interactions and protein functional associations, and identify protein complexes and proteins with multiple peptide mass fingerprints as input. The system takes Multiple Peptide Mass Fingerprints (PMFs) as a whole in the protein complex or protein identification. With the relations among proteins, it may greatly improve the accuracy of identification of protein complexes. Also, possible relationship of the multiple peptide mass fingerprints, such as ontology relation, can be discovered by our system, especially in the identification of protein complexes.
Computing motif correlations in proteins
(2003-12-01)
Horng, JT
;
Huang, HD
;
Wang, SH
;
Chen, MY
;
Huang, SL
Protein motifs, which are specific regions and conserved regions, are found by comparing multiple protein sequences. These conserved regions in general play an important role in protein functions and protein folds, for example, for their binding properties or enzymatic activities. The aim here is to find the existence correlations of protein motifs. The knowledge of protein motif/domain sharing should be important in shedding new light on the biologic functions of proteins and offering a basis in analyzing the evolution in the human genome or other genomes. The protein sequences used here are obtained from the PIR-NREF database and the protein motifs are retrieved from the PROSITE database. We apply data mining approach to discover the occurrence correlations of motif in protein sequences. The correlation of motifs mined can be used in evolution analyses and protein structure prediction. We discuss the latter, i.e., protein structure prediction in this study. The correlations mined are stored and maintained in a database system. The database is now available at http://bioinfo.csie.ncu.edu.tw/ProMotif/. (C) 2003 Wiley Periodicals, Inc.
Detection of discriminative sequence motifs in proteins obtained from prokaryotes grown at various temperatures
(2006-04-30)
Wu, LC
;
Horng, JT
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Huang, SL
;
Huang, HD
;
Liu, BJ
Recent investigations on the stability of proteins have demonstrated various structural factors, but few have considered sequence factors such as protein motifs. These motifs represent highly conserved regions and describe critical regions that may only exist on proteins that remain functional at high temperatures. This investigation presents a method for identifying and comparing corresponding mesophilic and thermophilic sequence motifs between protein families. Discriminative motifs that are conserved only in the mesophilic or thermophilic subfamily are identified. Analysis of the results shows that, although the subfamilies of most protein families share similar motifs, some discriminative motifs are present in particular thermophilic/mesophilic subfamilies. The thermophilic discriminative motifs are conserved only in thermophilic organisms, revealing that physiochemical principles support thermostability. (c) 2006 Wiley Periodicals, Inc.
Discovering common structural motifs of ribosomal RNA secondary structures in prokaryotes
(2005-08-01)
Huang, HD
;
Horng, JT
;
Wu, LC
;
Fang, SF
;
生物資訊及系統生物研究所
Certain structural motifs, like tetra-loops, in ribosomal RNA are known to functionally implicate in virtually every aspect of protein synthesis. Ribosomal RNA molecules were also widely used as a tool in molecular evolutionary studies because of their ubiquity, size and low evolutionary rate. In this study, we adapt a data mining approach to discover common structural motifs, and then we use a machine learning approach to identify discriminating CSMs from groups of organisms. Finally, we construct phylogeneitc trees to investigate the evolution of ribosomal RNA by serving the CSMs discovered as targets, which are used to estimate the evolutionary relatedness between organisms. The aim of this study is to discover common structural motifs (CSMs), i.e., those single-strain regions shared in ribosomal RNA secondary structures by several organisms, which are related to specific domains or functions. We discover a set of common structural motifs from several data sets of Archaea and Bacteria. Significant CSMs are then induced by a decision tree. Furthermore, phylogenetic trees are constructed based on CSMs and primary sequences of SSU 16 S ribosomal RNA.
i-Genome: A database to summarize oligonucleotide data in genomes
(2004-10-09)
Lin, FM
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Huang, HD
;
Chang, YC
;
Horng, JT
;
生物資訊及系統生物研究所
Background: Information on the occurrence of sequence features in genomes is crucial to comparative genomics, evolutionary analysis, the analyses of regulatory sequences and the quantitative evaluation of sequences. Computing the frequencies and the occurrences of a pattern in complete genomes is time-consuming. Results: The proposed database provides information about sequence features generated by exhaustively computing the sequences of the complete genome. The repetitive elements in the eukaryotic genomes, such as LINEs, SINEs, Alu and LTR, are obtained from Repbase. The database supports various complete genomes including human, yeast, worm, and 128 microbial genomes. Conclusions: This investigation presents and implements an efficiently computational approach to accumulate the occurrences of the oligonucleotides or patterns in complete genomes. A database is established to maintain the information of the sequence features, including the distributions of oligonucleotide, the gene distribution, the distribution of repetitive elements in genomes and the occurrences of the oligonucleotides. The database can provide more effective and efficient way to access the repetitive features in genomes.
Identifying the combination of genetic factors that determine susceptibility to cervical cancer
(2004-03-01)
Horng, JT
;
Hu, KC
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Wu, LC
;
Huang, HD
;
Lin, FM
Although infection with high-risk types of human papillomavirus (HPV) has been identified as the primary cause of cervical cancer, only some of those infected go on to develop cervical cancer. Obviously, the progression from HPV infection to cancer involves other environmental and host factors. Recent population-based twin and family studies have demonstrated the importance of the hereditary component of cervical cancer, associated with genetic susceptibility. Consequently, single-nucleotide polymorphism (SNP) markers and microsatellites should be considered genetic factors for determining what combinations of genetic factors are involved in precancerous changes to cervical cancer. This study employs a Bayesian network and four different decision tree algorithms, and compares the performance of these learning algorithms. The results of this study raise the possibility of investigations that could identify combinations of genetic factors, such as SNPs and microsatellites, that influence the risk associated with common complex multifactorial diseases, such as cervical cancer.
Identifying transcriptional regulatory sites in the human genome using an integrated computation
(2004)
Huang, HD
;
Horng, JT
;
Sun, YM
;
Tsou, AP
;
Huang, SL
Recently, biological databases and analytical methods have become available for analyzing gene expression and transcriptional regulatory sequences. However, users must make the complicated analyses to query the data in various databases, and to analyze the gene upstreams using various predictive tools. Beyond methods for predicting transcriptional regulatory sites, new automated and integrated methods for analyzing gene upstream sequences on a higher level are urgently required. We present an integrated system to predict transcriptional regulatory sites and detect co-occurrence of these regulatory sites after a set of genes are input. The system comprises a biological data warehousing system, patient discovery programs, pattern occurrence association detectors and user interfaces. User profiles and history pages enable users to trace the sequence analyses for transcriptional regulatory sites.
Identifying transcriptional regulatory sites in the human genome using an integrated system
(2004-03-01)
Huang, HD
;
Horng, JT
;
Sun, YM
;
Tsou, AP
;
Huang, SL
This work develops an integrated system which, after a set of genes are inputted, is able to predict transcriptional regulatory sites and to detect the co-occurrence of these regulatory sites. The system integrates several site detection methods such as known site matching, over-presented oligonucleotide detection and DNA motif discovery programs. User profiles and history pages enable users to trace the sequence analyses of these transcriptional regulatory sites. Two groups of co-regulated genes were used to test the proposed system. The results predicted by the proposed system consist of known site homologs and putative regulatory sites. By comparing these sites with previously published results, the proposed system is able to help biologists identify possible candidates for the regulatory sites from groups of co-regulated genes. The integrated system is now available at http://rgsminer. csie.ncu.edu.tw/.
Incorporating hidden Markov models for identifying protein kinase-specific phosphorylation sites
(2005-07-30)
Huang, HD
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Lee, TY
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Tzeng, SW
;
Wu, LC
;
Horng, JT
Protein phosphorylation, which is an important mechanism in posttranslational modification, affects essential cellular processes such as metabolism, cell signaling, differentiation, and membrane transportation. Proteins are phosphorylated by a variety of protein kinases. In this investigation, we develop a novel tool to computationally predict catalytic kinase-specific phosphorylation sites. The known phosphorylation sites from public domain data sources are categorized by their annotated protein kinases. Based on the concepts of profile Hidden Markov Models (HMM), computational models are trained from the kinase-specific groups of phosphorylation sites. After evaluating the trained models, we select the model with highest accuracy in each kinase-specific group and provide a Web-based prediction tool for identifying protein phosphorylation sites. The main contribution here is that we have developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity. (c) 2005 Wiley Periodicals, Inc.
KinasePhos: a web tool for identifying protein kinase-specific phosphorylation sites
(2005-07-01)
Huang, HD
;
Lee, TY
;
Tzeng, SW
;
Horng, JT
;
生物資訊及系統生物研究所
KinasePhos is a novel web server for computationally identifying catalytic kinase-specific phosphorylation sites. The known phosphorylation sites from public domain data sources are categorized by their annotated protein kinases. Based on the profile hidden Markov model, computational models are learned from the kinase-specific groups of the phosphorylation sites. After evaluating the learned models, the model with highest accuracy was selected from each kinase-specific group, for use in a web-based prediction tool for identifying protein phosphorylation sites. Therefore, this work developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity. The prediction tool is freely available at http://KinasePhos.mbc. nctu.edu.tw/.
MultiProtident: Identifying proteins using database search and protein-protein interactions
(2005-05-01)
Huang, HD
;
Lee, TY
;
Wu, LC
;
Lin, FM
;
Juan, HF
Protein identification is important in proteomics. Proteomic analyses based on mass spectra (MS) constitute innovative ways to identify the components of protein complexes. Instruments can obtain the mass spectrum to an accuracy of 0.01 Da or better, but identification errors are inevitable. This study shows a novel tool, MultiProtldent, which can identify proteins using additional information about protein-protein interactions and protein functional associations. Both single and multiple Peptide Mass Fingerprints (PMFs) are input to MultiProtldent, which matches the PMFs to a theoretical peptide mass database. The relationships or interactions among proteins are considered to reduce false positives in PMF matching. Experiments to identify protein complexes reveal that MultiProtldent is highly promising. The website associated with this study is http://dbms104.csie.ncu.edu.tw/.
Optical coating designs using the family competition evolutionary algorithm
(2001-12-01)
Yang, JM
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Horng, JT
;
Lin, CJ
;
Kao, CY
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生物科技學系
A robust evolutionary approach, called the Family Competition Evolutionary Algorithm (FCEA), is described for the synthesis of optical thin-film designs. Based on family competition and adaptive rules, the proposed approach consists of global and local strategies by integrating decreasing mutations and self-adaptive mutations. The method is applied to three different optical coating designs with complex spectral quantities. Numerical results indicate that the proposed approach performs very robustly and is very competitive with other approaches.
RgS-Miner: A biological data warehousing, analyzing and mining system for identifying transcriptional regulatory sites in human genome
(2004)
Sun, YM
;
Huang, HD
;
Horng, JT
;
Tsou, AP
;
Huang, SL
Recently, biological databases and. analytical methods have become available for analyzing gene expression and transcriptional regulatory sequences. However, users must make the complicated analyses to query the data in various databases, and then they must analyze the gene upstreams using various predictive tools, before finally converting date among formats. Beyond methods for predicting transcriptional regulatory sites, new automated and integrated methods for analyzing gene upstream sequences on a higher level are urgently required. Efficient and integrated data management methods are essential, too. We present an integrated system, namely RgS-Miner, to predict transcriptional regulatory sites and detect co-occurrence of these regulatory sites. RgS-Miner comprises a biological data,, warehousing system, pattern discovery programs, pattern occurrence association detectors and user interfaces. The system is available at http://rgsminer.csie.ncu.edu.tw/.
SpliceInfo: an information repository for mRNA alternative splicing in human genome
(2005-01-01)
Huang, HD
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Horng, JT
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Lin, FM
;
Chang, YC
;
Huang, CC
We have developed an information repository named SpliceInfo to collect the occurrences of the four major alternative-splicing (AS) modes in human genome; these include exon skipping, 5'-alternative splicing, 3'-alternative splicing and intron retention. The dataset is derived by comparing the nucleotide and protein sequences available for a given gene for evidence of AS. Additional features such as the tissue specificity of the mRNA, the protein domain contained by exons, the GC-ratio of exons, the repeats contained within the exons, and the Gene Ontology are annotated computationally for each exonic region that is alternatively spliced. Motivated by a previous investigation of AS-related motifs such as exonic splicing enhancer and exonic splicing silencer, this resource also provides a means of identifying motifs candidates and this should help to identify potential regulatory mechanisms within a particular exonic sequence set and its two flanking intronic sequence sets. This is carried out using motif discovery tools to identify motif candidates related to alternative splicing regulation and together with a secondary structure prediction tool, will help in the identification of the structural properties of such regulatory motifs. The integrated resource is now available on http://Spliceinfo.mbc.NCTU.edu.tw/.