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Search Results: 1 - 10 of 44399 matches for " Chuan-Yi Tang "
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Phylogenomic and Domain Analysis of Iterative Polyketide Synthases in Aspergillus Species
Shu-Hsi Lin, Miwa Yoshimoto, Ping-Chiang Lyu, Chuan-Yi Tang and Masanori Arita
Evolutionary Bioinformatics , 2012, DOI: 10.4137/EBO.S9796
Abstract: Aspergillus species are industrially and agriculturally important as fermentors and as producers of various secondary metabolites. Among them, fungal polyketides such as lovastatin and melanin are considered a gold mine for bioactive compounds. We used a phylogenomic approach to investigate the distribution of iterative polyketide synthases (PKS) in eight sequenced Aspergilli and classified over 250 fungal genes. Their genealogy by the conserved ketosynthase (KS) domain revealed three large groups of nonreducing PKS, one group inside bacterial PKS, and more than 9 small groups of reducing PKS. Polyphyly of nonribosomal peptide synthase (NRPS)-PKS genes raised questions regarding the recruitment of the elegant conjugation machinery. High rates of gene duplication and divergence were frequent. All data are accessible through our web database at http://metabolomics.jp/wiki/Category:PK.
3D-QSAR Study for Checkpoint Kinase 2 Inhibitors through Pharmacophore Hypotheses
Yen-Ling Wang,Chun-Yuan Lin,Kuei-Chung Shih,Chuan-Yi Tang
International Journal of Chemical Engineering and Applications , 2013, DOI: 10.7763/ijcea.2013.v4.263
Abstract: DNA-damage is induced by ionizing radiation, genotoxic chemicals or collapsed replication forks. To prevent and repair the DNA-damage, mammalian cells will control and stabilize the genome by cell cycle checkpoint. Checkpoint kinase 2 (Chk2) is one of the important kinases that has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. Hence, in this study, we will concentrate on Chk2 and the purpose is to build the pharmacophore hypotheses (PhModels) by 3D-QSAR study which can identify inhibitors with high biological activities. Ten PhModels were generated by the HypoGen Best algorithm. The established PhModel, Hypo01, was evaluated in the cost function analysis of its correlation coefficient (r), RMS, cost difference, and configuration cost, with the values: 0.955, 1.28, 192.51, and 16.07, respectively. The result of Fischer’s cross-validation test for Hypo01 model yielded a 95% confidence level, and the correlation coefficient (rtest) of the testing set yielded a best value of 0.81.
Phylogenomic and Domain Analysis of Iterative Polyketide Synthases in Aspergillus Species
Shu-Hsi Lin,Miwa Yoshimoto,Ping-Chiang Lyu,Chuan-Yi Tang
Evolutionary Bioinformatics , 2012,
Abstract:
Development of a Human Dihydroorotate Dehydrogenase (hDHODH) Pharma-Similarity Index Approach with Scaffold-Hopping Strategy for the Design of Novel Potential Inhibitors
Kuei-Chung Shih, Chi-Ching Lee, Chi-Neu Tsai, Yu-Shan Lin, Chuan-Yi Tang
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0087960
Abstract: Human dihydroorotate dehydrogenase (hDHODH) is a class-2 dihydroorotate dehydrogenase. Because it is extensively used by proliferating cells, its inhibition in autoimmune and inflammatory diseases, cancers, and multiple sclerosis is of substantial clinical importance. In this study, we had two aims. The first was to develop an hDHODH pharma-similarity index approach (PhSIA) using integrated molecular dynamics calculations, pharmacophore hypothesis, and comparative molecular similarity index analysis (CoMSIA) contour information techniques. The approach, for the discovery and design of novel inhibitors, was based on 25 diverse known hDHODH inhibitors. Three statistical methods were used to verify the performance of hDHODH PhSIA. Fischer’s cross-validation test provided a 98% confidence level and the goodness of hit (GH) test score was 0.61. The q2, r2, and predictive r2 values were 0.55, 0.97, and 0.92, respectively, for a partial least squares validation method. In our approach, each diverse inhibitor structure could easily be aligned with contour information, and common substructures were unnecessary. For our second aim, we used the proposed approach to design 13 novel hDHODH inhibitors using a scaffold-hopping strategy. Chemical features of the approach were divided into two groups, and the Vitas-M Laboratory fragment was used to create de novo inhibitors. This approach provides a useful tool for the discovery and design of potential inhibitors of hDHODH, and does not require docking analysis; thus, our method can assist medicinal chemists in their efforts to identify novel inhibitors.
Feature Identification of Compensatory Gene Pairs without Sequence Homology in Yeast
Chien-Hua Peng,Shu-Hsi Lin,Shih-Chi Peng,Ping-Chiang Lyu,Masanori Arita,Chuan-Yi Tang
Comparative and Functional Genomics , 2012, DOI: 10.1155/2012/653174
Abstract: Genetic robustness refers to a compensatory mechanism for buffering deleterious mutations or environmental variations. Gene duplication has been shown to provide such functional backups. However, the overall contribution of duplication-based buffering for genetic robustness is rather small. In this study, we investigated whether transcriptional compensation also exists among genes that share similar functions without sequence homology. A set of nonhomologous synthetic-lethal gene pairs was assessed by using a coexpression network, protein-protein interactions, and other types of genetic interactions in yeast. Our results are notably different from those of previous studies on buffering paralogs. The low expression similarity and the conditional coexpression alone do not play roles in identifying the functionally compensatory genes. Additional properties such as synthetic-lethal interaction, the ratio of shared common interacting partners, and the degree of coregulation were, at least in part, necessary to extract functional compensatory genes. Our network-based approach is applicable to select several well-documented cases of compensatory gene pairs and a set of new pairs. The results suggest that transcriptional reprogramming plays a limited role in functional compensation among nonhomologous genes. Our study aids in understanding the mechanism and features of functional compensation more in detail.
Hydrophilic Aromatic Residue and in silico Structure for Carbohydrate Binding Module
Wei-Yao Chou, Tun-Wen Pai, Ting-Ying Jiang, Wei-I Chou, Chuan-Yi Tang, Margaret Dah-Tsyr Chang
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0024814
Abstract: Carbohydrate binding modules (CBMs) are found in polysaccharide-targeting enzymes and increase catalytic efficiency. Because only a relatively small number of CBM structures have been solved, computational modeling represents an alternative approach in conjunction with experimental assessment of CBM functionality and ligand-binding properties. An accurate target-template sequence alignment is the crucial step during homology modeling. However, low sequence identities between target/template sequences can be a major bottleneck. We therefore incorporated the predicted hydrophilic aromatic residues (HARs) and secondary structure elements into our feature-incorporated alignment (FIA) algorithm to increase CBM alignment accuracy. An alignment performance comparison for FIA and six others was made, and the greatest average sequence identities and similarities were achieved by FIA. In addition, structure models were built for 817 representative CBMs. Our models possessed the smallest average surface-potential z scores. Besides, a large true positive value for liagnd-binding aromatic residue prediction was obtained by HAR identification. Finally, the pre-simulated CBM structures have been deposited in the Database of Simulated CBM structures (DS-CBMs). The web service is publicly available at http://dscbm.life.nthu.edu.tw/ and http://dscbm.cs.ntou.edu.tw/.
HaplotypeCN: Copy Number Haplotype Inference with Hidden Markov Model and Localized Haplotype Clustering
Yen-Jen Lin, Yu-Tin Chen, Shu-Ni Hsu, Chien-Hua Peng, Chuan-Yi Tang, Tzu-Chen Yen, Wen-Ping Hsieh
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0096841
Abstract: Copy number variation (CNV) has been reported to be associated with disease and various cancers. Hence, identifying the accurate position and the type of CNV is currently a critical issue. There are many tools targeting on detecting CNV regions, constructing haplotype phases on CNV regions, or estimating the numerical copy numbers. However, none of them can do all of the three tasks at the same time. This paper presents a method based on Hidden Markov Model to detect parent specific copy number change on both chromosomes with signals from SNP arrays. A haplotype tree is constructed with dynamic branch merging to model the transition of the copy number status of the two alleles assessed at each SNP locus. The emission models are constructed for the genotypes formed with the two haplotypes. The proposed method can provide the segmentation points of the CNV regions as well as the haplotype phasing for the allelic status on each chromosome. The estimated copy numbers are provided as fractional numbers, which can accommodate the somatic mutation in cancer specimens that usually consist of heterogeneous cell populations. The algorithm is evaluated on simulated data and the previously published regions of CNV of the 270 HapMap individuals. The results were compared with five popular methods: PennCNV, genoCN, COKGEN, QuantiSNP and cnvHap. The application on oral cancer samples demonstrates how the proposed method can facilitate clinical association studies. The proposed algorithm exhibits comparable sensitivity of the CNV regions to the best algorithm in our genome-wide study and demonstrates the highest detection rate in SNP dense regions. In addition, we provide better haplotype phasing accuracy than similar approaches. The clinical association carried out with our fractional estimate of copy numbers in the cancer samples provides better detection power than that with integer copy number states.
Feature Identification of Compensatory Gene Pairs without Sequence Homology in Yeast
Chien-Hua Peng,Shu-Hsi Lin,Shih-Chi Peng,Ping-Chiang Lyu,Masanori Arita,Chuan-Yi Tang
International Journal of Genomics , 2012, DOI: 10.1155/2012/653174
Abstract: Genetic robustness refers to a compensatory mechanism for buffering deleterious mutations or environmental variations. Gene duplication has been shown to provide such functional backups. However, the overall contribution of duplication-based buffering for genetic robustness is rather small. In this study, we investigated whether transcriptional compensation also exists among genes that share similar functions without sequence homology. A set of nonhomologous synthetic-lethal gene pairs was assessed by using a coexpression network, protein-protein interactions, and other types of genetic interactions in yeast. Our results are notably different from those of previous studies on buffering paralogs. The low expression similarity and the conditional coexpression alone do not play roles in identifying the functionally compensatory genes. Additional properties such as synthetic-lethal interaction, the ratio of shared common interacting partners, and the degree of coregulation were, at least in part, necessary to extract functional compensatory genes. Our network-based approach is applicable to select several well-documented cases of compensatory gene pairs and a set of new pairs. The results suggest that transcriptional reprogramming plays a limited role in functional compensation among nonhomologous genes. Our study aids in understanding the mechanism and features of functional compensation more in detail. 1. Introduction Genetic robustness is critical for enhancing organism’s capability to tolerate random mutations [1]. One of the features for biological robustness is functional redundancy, in which two or more components can perform similar functions [2]. From a theoretical perspective, two main mechanisms have been proposed for explaining biological robustness due to functional redundancy [3]. The first mechanism is duplicate buffering [4, 5], which is a backup compensation for the loss or mutation of a duplicate (paralog), to overcome stochastic fluctuations in gene and protein expression [3–6]. This has been considered as an obvious source of genetic redundancy that can compensate for a gene loss [4, 5, 7, 8]. More specifically, if gene A and gene B are functionally redundant duplicates, the expression of gene B will be upregulated to rescue the organism upon the mutation of gene A [6]. However, functionally redundant duplicates are evolutionarily unfavorable [9]. The capability to compensate for gene mutations may be lost over long periods because of divergence [9–14]. The second mechanism stems from the viewpoint of distributed robustness, usually
Design of occlusion pressure testing system for infusion pump  [PDF]
Peng Zhang, Shu-Yi Wang, Chuan-Yi Yu, Min-Yan Zhang
Journal of Biomedical Science and Engineering (JBiSE) , 2009, DOI: 10.4236/jbise.2009.26062
Abstract: Reliability of medical devices such as infusion pumps is extremely important because these devices are being used in patients who are in critical condition. Occlusion pressure, as an important parameter of infusion pumps, should be detected when an occlusion occurred. How-ever, infusion pumps’ occlusion pressure could not be tested and the performance of these pumps is not known to us. In order to test the occlusion pressure of infusion pump, a testing system has been put forward according to standards of IEC 60601-2-24:1998/ GB 9706.27- 2005. The system is comprised of sensor, acquisition card, three-way tap and so on; this system is controlled by a PC. At the same time, sampling rate could be changed if necessary and test time could be recorded. And then the characteristics of this system were studied, such as linear, effects of pump rates and different pumps. The system remained linear in a given environment. The higher is the pump rate, the faster is the time to reach occlusion condi-tion. The testing system has been proved to be effective in testing the occlusion pressure of infusion pumps and the accuracy error of pressure is content the demand of ±1% of range.
A reinforced merging methodology for mapping unique peptide motifs in members of protein families
Hao-Teng Chang, Tun-Wen Pai, Tan-chi Fan, Bo-Han Su, Pei-Chih Wu, Chuan-Yi Tang, Chun-Tien Chang, Shi-Hwei Liu, Margaret Chang
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-38
Abstract: We have developed a reinforced merging algorithm (RMA) with which non-gapped UPMs were identified in a variety of query protein sequences including members of human ribonuclease A (RNaseA), epidermal growth factor receptor (EGFR), matrix metalloproteinase (MMP), and Sma-and-Mad related protein families (Smad). The UPMs generally occupy specific positions in the resolved 3-D structures, especially the loop regions on the structural surfaces. These motifs coincide with the recognition sites for antibodies, as the epitopes of four monoclonal antibodies and two polyclonal antibodies were shown to overlap with the UPMs. Most of the UPMs were found to correlate well with the potential antigenic regions predicted by PROTEAN. Furthermore, an accuracy of 70% can be achieved in terms of mapping a UPM to an epitope.Our study provides a bioinformatic approach for searching and predicting potential epitopes and interacting motifs that distinguish different members of a protein family.Multiple protein sequence comparison can provide a valuable protein signature and, thus, contribute to the fields of structural biology and molecular evolution [1,2]. In general, sequence similarity identified by multiple sequence alignment (MSA) among a set of query sequences suggests similar function among the proteins [3]. These signatures can be readily obtained by web-based tools, such as BLAST [4], CLUSTALW [5], or MUSCA [6] systems. However, although the default parameters in most programs give satisfactory results, in some cases special variables need to be taken into consideration. For example, the allocation of major variations among a few query sequences can be achieved from the results of direct MSA, whereas the uniqueness of each sequence that is not well-aligned is difficult to reveal. It is also quite expensive and time-consuming to experimentally search for such unique peptide motifs (UPMs) that may involve the key biological functions of interest. Therefore, the need for effective a
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